essay about social influence

Social Influence Revision Notes

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Social influence is the process by which an individual’s attitudes, beliefs or behavior are modified by the presence or action of others. Four areas of social influence are conformity, compliance and obedience, and minority influence.

Conformity (Majority Influence)

Conformity is a type of social influence defined as a change in belief or behavior in response to real or imagined social pressure. It is also known as majority influence.

Types of Conformity

Compliance ao1.

This refers to instances where a person may agree in public with a group of people, but the person privately disagrees with the group’s viewpoint or behavior. The individual changes their views, but it is a temporary change.

For example, a person may laugh at a joke because their group of friends find it funny but deep down the person does not find the joke funny.

For a study on compliance refer to Asch’s Line Study .

Internalisation AO1

Publicly changing behavior to fit in with the group while also agreeing with them privately. An internal (private) and external (public) change of behavior. This is the deepest level of conformity were the beliefs of the group become part of the individual’s own belief system.

An example of internalisation is if someone lived with a vegetarian at university and then decides to also become one too because they agree with their friend’s viewpoint / someone converting religions would also be a good example.

For a study on internalisation refer to Jenness (see below).

Identification AO1

Identification occurs when someone conforms to the demands of a given social role in society. For example, a policeman, teacher or politician. This type of conformity extends over several aspects of external behavior. However, there still be no changed to internal personal opinion.

A good example is Zimbardo’s prison study .

AO2 Scenario Question

Jan and Norah have just finished their first year at university where they lived in a house with six other students. All the other students were very health conscious and ate only organic food. Jan had listened to their point of view and now she also eats only organic food.

Norah was happy to eat organic food while in the house, but when she went home for the holidays she ate whatever her mother cooked. Both girls conformed, but for different reasons.

Explain which type of conformity each girl was showing.

“Jan shows internalisation. She has publicly and privately changed her attitudes and now permanently only eats organic food. Norah is showing compliance. She only conformed publicly to her friends’ behavior but had obviously not privately undergone attitude change to eating organic as she reverted to eating non-organic in the holidays. Norah probably conformed to gain group approval and membership whereas Jan believed the other students to be ‘right’ in their belief that organic food was ‘good’.”

Explanations for Conformity

Normative influence (ao1/ao3).

Normative social influence is where a person conforms to fit in with the group because they don’t want to appear foolish or be left out. Normative social influence is usually associated with compliance,

where a person changes their public behavior but not their private beliefs.

For example, a person may feel pressurised to smoke because the rest of their friends are. Normative Social influence tends to lead to compliance because the person smokes just for show but deep down they wish not to smoke. This means any change of behavior is temporary .

For a study on normative influence refer to Asch .

Informational Influence (AO1/AO3)

Informational social influence is where a person conforms because they have a desire to be right , and look to others who they believe may have more information.

This type of conformity occurs when a person is unsure of a situation or lacks knowledge and is associated with internalisation .

An example of this is if someone was to go to a posh restaurant for the first time, they may be confronted with several forks and not know which one to use, so they might look to a near by person to see what fork to use first.

For a study on informational influence refer to Jenness (see below).

Jenness’ Bean Jar Experiment AO1

Jenness carried out a study into conformity – in his experiment participants were asked to estimate how many beans they thought were in a jar. Each participant had to make an individual estimate, and then do the same as a group.

He found that when the task was carried out in a social group, the participants would report estimates of roughly the same value (even though they had previously reported quite different estimates as individuals).

The study was successful in showing majority influence, thus proving that individuals” behavior and beliefs can be influenced by a group. Additionally, this is likely to be an example of informational social influence as participants would be uncertain about the actual number of beans in the jar.

Variables Affecting Conformity

Asch’s line study ao1.

Asch wanted to investigate whether people would conform to the majority in situations where an answer was obvious.

Procedure : In Asch’s study there were 5-7 participants per group. Each group was presented with a standard line and three comparison lines. Participants had to say aloud which comparison line matched the standard line in length. In each group there was only one real participant the remaining 6 were confederates. The confederates were told to give the incorrect answer on 12 out of 18 trails.

Results : Real participants conformed on 32% of the critical trials where confederates gave the wrong answers. Additionally, 75% of the sample conformed to the majority on at least one trial.

Evaluation of Asch’s Study AO3

• This study lacks ecological validity as it was based on peoples’ perception of lines, this does not reflect the complexity of real life conformity.
• There are also sampling issues regarding this study as the study was only carried out on men thus the sample was gender bias and therefore the results cannot be applied to females. The sample therefore lacks population validity.
• Moreover, there are ethical issues regarding Asch’s study – Mention deception as participants were told the study was about perception of lines. As a result, they could not give informed consent. Furthermore, it is possible that the participants may have felt embarrassed when the true nature of the study was revealed. Thus could potentially put them through some form of psychological harm. However, Asch did debrief at the end.
• For extra AO3 points link Asch’s results to theories/reasons why people may conform to the majority. For instance, some participants said they conformed to fit in with the group, this claim coincides (supports) ‘Normative influence’ which states that people conform to fit in when privately disagreeing with the majority.

Factors Affecting Conformity AO3

In further trials, Asch (1952, 1956) changed the procedure (i.e., independent variables) to investigate which situational factors influenced the level of conformity (dependent variable).  His results and conclusions are given below:

Asch altered the number of confederates in his study to see how this effected conformity. The bigger the majority group (number of confederates), the more people conformed, but only up to a certain point.

With one other person (i.e., confederate) in the group conformity was 3%, with two others it increased to 13%, and with three or more it was 32% (or 1/3). However, conformity did not increase much after the group size was about 4/5.

Because conformity does not seem to increase in groups larger than four, this is considered the optimal group size.

Brown and Byrne (1997) suggest that people might suspect collusion if the majority rises beyond three or four.

According to Hogg & Vaughan (1995), the most robust finding is that conformity reaches its full extent with 3-5 person majority, with additional members having little effect.

Group Unanimity

A person is more likely to conform when all members of the group agree and give the same answer.

When one other person in the group gave a different answer from the others, and the group answer was not unanimous, conformity dropped. Asch (1951) found that even the presence of just one confederate that goes against the majority choice can reduce conformity as much as 80%.

Difficulty of Task

When the (comparison) lines (e.g., A, B, C) were made more similar in length it was harder to judge the correct answer and conformity increased.

When we are uncertain, it seems we look to others for confirmation. The more difficult the task, the greater the conformity.

Answer in Private

When participants were allowed to answer in private (so the rest of the group does not know their response) conformity decreases. This is because there are fewer group pressures and normative influence is not as powerful, as there is no fear of rejection from the group.

Conformity to Social Roles

Social roles are the part people play as members of a social group (e.g. student, teacher, policeman etc). There is considerable pressure to conform to the expectations of a social role. Conforming to a social role is called identification.

Stanford Prison Experiment AO1

Zimbardo wanted to investigate how readily people would conform to the social roles of guard and prisoner in a role-playing exercise that simulated prison life.

Procedure : To study the roles people play in prison situations, Zimbardo converted a basement of the Stanford University psychology building into a mock prison.

He advertised for students to play the roles of prisoners and guards for a fortnight. Participants were randomly assigned to either the role of prisoner or guard in a simulated prison environment.

Prisoners were issued a uniform, and referred to by their number only. Guards were issued a khaki uniform, together with whistles, handcuffs and dark glasses, to make eye contact with prisoners impossible. The guards worked shifts of eight hours each (the other guards remained on call). No physical violence was permitted.

Zimbardo observed the behavior of the prisoners and guards (as a researcher), and also acted as prison warden.

Findings : Within a very short time both guards and prisoners were settling into their new roles, with the guards adopting theirs quickly and easily. Within hours of beginning the experiment some guards began to harass prisoners. T

hey behaved in a brutal and sadistic manner, apparently enjoying it. Other guards joined in, and other prisoners were also tormented.

The prisoners soon adopted prisoner-like behavior too. They talked about prison issues a great deal of the time. They ‘told tales’ on each other to the guards. They started taking the prison rules very seriously, and some even began siding with the guards against prisoners who did not obey the rules.

As the prisoners became more submissive, the guards became more aggressive and assertive. They demanded ever greater obedience from the prisoners.

The prisoners were dependent on the guards for everything so tried to find ways to please the guards, such as telling tales on fellow prisoners.

Evaluation of Zimbardo’s Study AO3

• Demand characteristics could explain the findings of the study. Most of the guards later claimed they were simply acting. Because the guards and prisoners were playing a role their behavior may not be influenced by the same factors which affect behavior in real life. This means the study’s findings cannot be reasonably generalized to real life, such as prison settings. I.e the study has low ecological validity.
• The study may also lack population validity as the sample comprised US male students. The study’s findings cannot be applied to female prisons or those from other countries. For example, America is an individualist culture (were people are generally less conforming) and the results maybe different in collectivist cultures (such as Asian countries) .
• A strength of the study is that it has altered the way US prisons are run. For example, juveniles accused of federal crimes are no longer housed before trial with adult prisoners (due to the risk of violence against them).
• The study has received many ethical criticisms, including lack of fully informed consent by participants as Zimbardo himself did not know what would happen in the experiment (it was unpredictable). Also, the prisoners did not consent to being “arrested” at home.
• Also, participants playing the role of prisoners were not protected from psychological harm, experiencing incidents of humiliation and distress. For example, one prisoner had to be released after 36 hours because of uncontrollable bursts of screaming, crying and anger. However, in Zimbardo’s defence the emotional distress experienced by the prisoners could not have been predicted from the outset. In addition Zimbardo did conduct debriefing sessions for several years afterwards and concluded they were no lasting negative effects.
• Another strength of the study is that the harmful treatment of participant led to the formal recognition of ethical guidelines . Studies must now gain ethical approval before they are conducted. An ethics committee review whether the potential benefits of the research are justifiable in the light of possible risk of physical or psychological harm. They may request researchers make changes to the studies design or procedure, or in extreme cases deny approval of the study altogether.

Obedience is a type of social influence where a person follows an order from another person who is usually an authority figure.

Explanations for Obedience

Milgram’s shock study ao1.

Milgram wanted to know why Germans were willing to kill Jews during the Holocaust. He thought that it might have been because German’s were just evil.

He thought that Americans were different and would not have followed such orders. To test this ‘German’s are different’ hypothesis he carried out this study (outlined below).

Procedure : Milgram wanted to see whether people would obey a legitimate authority figure when given instructions to harm another human being.

He conducted a lab experiment in which two participants were assigned either the role of a teacher (this was always given to the true participant) or learner (a confederate called Mr. Wallace).

The teacher and learner were put into separate rooms. The teacher was then asked by the experimenter (who wore a lab coat) to administer electric shocks (which were actually harmless) to the learner each time he gave the wrong answer. These shocks increased every time the learner gave a wrong answer, from 15 – 450 volts.

The experimenter (Mr Williams) wore a grey lab coat and his role was to give a series of orders / prods when the participant refused to administer a shock. There were 4 prods and if one was not obeyed then the experimenter read out the next prod, and so on.

• Prod 1: please continue.
• Prod 2: the experiment requires you to continue.
• Prod 3: It is absolutely essential that you continue.
• Prod 4: you have no other choice but to continue.

Results : The results were that all participants went to 300 volts and 65% were willing to go all the way to 450 volts. Milgram did more than one experiment – he carried out 18 variations of his study.

All he did was alter the situation (IV) to see how this affected obedience (DV). For example, when the experimenter instructed and prompted the teacher by telephone from another room, obedience fell to 20.5%.

Evaluation of Milgram’s Study AO3

• A limitation is that this study lacked ecological validity as it was carried out in a lab under artificial conditions. This means that it might not be possible to generalise the finding to a real life setting, as people do not usually receive orders to hurt another person in real life.
• Another problem is that the sample was biased. Milgram only used males in his study and this means we cannot generalise the results to females.
• Highlight the value that Milgram’s work has provided to social Psychology. For instance Milgram’s work gives an insight into why people under the Nazi reign were willing to kill Jews when given orders to do so. It also highlights how we can all be blind to obedience often doing things without question.
• A strength of the study is that it used a standardised procedure because it was a lab experiment. This is good because it improves the reliability of the study and also helps establish a causal relationship.

Ethical Issues AO3

• Deception – the participants actually believed they were shocking a real person, and were unaware the learner was a confederate of Milgram’s.

However, Milgram argued that “illusion is used when necessary in order to set the stage for the revelation of certain difficult-to-get-at-truths”.

Milgram also interviewed participants afterwards to find out the effect of the deception. Apparently 83.7% said that they were “glad to be in the experiment”, and 1.3% said that they wished they had not been involved.

• Protection of participants – Participants were exposed to extremely stressful situations that may have the potential to cause psychological harm. Many of the participants were visibly distressed.

Signs of tension included trembling, sweating, stuttering, laughing nervously, biting lips and digging fingernails into palms of hands. Three participants had uncontrollable seizures, and many pleaded to be allowed to stop the experiment.

Full blown seizures were observed for 3 participants; one so violent that the experiment was stopped.

In his defence, Milgram argued that these effects were only short term. Once the participants were debriefed (and could see the confederate was OK) their stress levels decreased. Milgram also interviewed the participants one year after the event and concluded that most were happy that they had taken part.

• However, Milgram did debrief the participants fully after the experiment and also followed up after a period of time to ensure that they came to no harm.

The Agentic State

Agency theory says that people will obey an authority when they believe that the authority will take responsibility for the consequences of their actions. This is supported by some aspects of Milgram’s evidence.

For example, when participants were reminded that they had responsibility for their own actions, almost none of them were prepared to obey. In contrast, many participants who were refusing to go on did so if the experimenter said that he would take responsibility’.

Another example of the agenetic state involved a variation of Milgram’s study whereby participants could instruct an assistant (confederate) to press the switches. In this condition 92.5% shocked to the maximum 450 volts. This shows when there is less personal responsibility obedience increases.

Limitations AO3

• Cannot explain Nazi behavior – Mandel described how the German Police Reserve shot civilians in a small Polish town even though they were not directly ordered to and were told they could be assigned to other duties – Challenges agentic state as they were not powerless to obey.
• May be better explained by ‘plain cruelty’ – Zimbardo’s participants may have used the situation to express their sadistic tendencies, guards inflicted rapidly escalating cruelty to prisoners even though there was no authority figure telling them to – Obedience may be caused by certain aspects of human nature.

Legitimacy of Authority Figure

Most societies are hierarchal (parents, teachers and police officers hold authority over us). The authority they use is legitimate as it is argued by society, helping it to run smoothly. One of the consequences is that some people are granted the power to punish others.

People tend to obey others if they recognise their authority as morally right and / or legally based (i.e. legitimate). This response to legitimate authority is learned in a variety of situations, for example in the family, school and workplace.

With regard to Milgram” study the experimenter is seen as having legitimate authority as he has scientific status.

If an authority figure’s commands are potentially harmful, for it to be perceived as legitimate they must occur within some type of institutional structure (e.g. a university or the military).

Situational Factors

The Milgram experiment was carried out many times whereby Milgram varied the basic procedure (changed the IV). By doing this Milgram could identify which situational factors affected obedience (the DV).

Obedience was measured by how many participants shocked to the maximum 450 volts (65% in the original study).

Authority Figure Wearing a Uniform

Milgram’s experimenter (Mr. Williams) wore a laboratory coat (a symbol of scientific expertise) which gave him a high status. But when the experimenter dressed in everyday clothes obedience was very low. The uniform of the authority figure can give them status.

Status of Location

Milgram’s obedience experiment was conducted at Yale, a prestigious university in America. The high status of the university gave the study credibility and respect in the eyes of the participants, thus making them more likely to obey.

When Milgram moved his experiment to a set of run down offices rather than the impressive Yale University obedience dropped to 47.5%. This suggests that status of location effects obedience.

Proximity of Authority Figure

People are more likely be obey an authority figure who is in close proximity (i.e. nearby). In Milgram’s study the experimenter was in the same room as the participant (i.e. teacher).

If the authority figure is distant it is easier to resistant their orders. When the experimenter instructed and prompted the teacher by telephone from another room, obedience fell to 20.5%. Many participants cheated and missed out shocks or gave less voltage than ordered to by the experimenter.

Dispositional Explanation: Authoritarian Personality

Adorno felt that personality (i.e. dispositional) factors rather than situational (i.e. environmental) factors could explain obedience. He proposed that there was such a thing as an authoritarian personality, i.e. a person who favours an authoritarian social system and, admires obedience to authority figures.

One of the various characteristics of the authoritarian personality is that the individual is hostile to those who are of inferior status, but obedient of people with high status.

He investigated 2000 middle class, white Americans and their unconscious attitudes towards other racial groups using the F-scale to measure authoritarian personality

• Adorno found many significant correlations (e.g. Authoritarianism correlated with prejudice against minority groups) but we cannot say that one variable causes another – Adorno cannot claim that a harsh parenting style caused a development of an Authoritarian personality, we must consider other explanations like legitimacy of authority.
• Millions of individuals in Germany displayed obedient behavior but didn’t have the same personality, it is unlikely that the majority of Germany’s population possessed an authoritarian personality – An alternative explanation like social identity theory (people identify with groups they are apart with and discriminate against ones they are not) may be more realistic.
• May be better explanations – Prejudice and submissiveness could just as easily be caused by a poor standard of education as a child – Theory lacks internal validity as it assumes obedience is caused by dispositional explanations when it may be situational variables.
• Adorno used a biased sample – Only used 2000 middle class white Americans who are more likely to have an Authoritarian personality due to demographics and the time of the study – Research lacks population validity and historical validity, so conclusions cannot be generalised to people outside the sample.

Resistance to Social Influence

Independent behavior is a term that psychologists use to describe behavior that seems not be influenced by other people. This happens when a person resists the pressures to conform or obey.

Social Support

In one of Asch’s experimental variations he showed that the presence of a dissident (a confederate who did not conform) led to a decrease in the conformity levels in true participants.

This is thought to be because the presence of a dissident gave the true participant social support and made them feel more confident in their own decision and more confident in rejecting the majority position.

Social support also decreases obedience to authority. In a variation of Milgram” study two other participants (confederates) were also teachers but refused to obey. Confederate 1 stopped at 150 volts and confederate 2 stopped at 210 volts. The presence of others who are seen to disobey the authority figure reduced the level of obedience to 10%.

Locus of Control

The term ‘ Locus of control ’ refers to how much control a person feels they have in their own behavior. A person can either have an internal locus of control or an external locus of control.

There is a continuum, with most people lying in between.

People with a high internal locus of control perceive (see) themselves as having a great deal of personal control over their behavior and are therefore more likely to take responsibility for the way they behave. For example, I did well on the exams because I revised extremely hard.

In contrast a person with a high external locus of control perceive their behaviors as being a result of external influences or luck – e.g. I did well on the test because it was easy.

Research has shown that people with an internal locus of control tend to be less conforming and less obedient (i.e. more independent). Rotter proposes that people with internal locus of control are better at resisting social pressure to conform or obey, perhaps because they feel responsible for their actions.

Minority Influence

Minority influence occurs when a small group (minority) influences the opinion of a much larger group (majority). This can happen when the minority behaves in the following ways.

Consistency

Moscovici stated that being consistent and unchanging in a view is more likely to influence the majority than if a minority is inconsistent and chops and changes their mind.

Procedure : Moscovici conducted an experiment in which female participants were shown 36 blue slides of different intensity and asked to report the colours. There were two confederates (the minority) and four participants (the majority).

In the first part of the experiment the two confederates answered green for each of the 36 slides. They were totally consistent in their responses. In the second part of the experiment they answered green 24 times and blue 12 times. In this case they were inconsistent in their answers. A control group was also used consisting of participants only – no confederates.

Findings : When the confederates were consistent in their answers about 8% of participants said the slides were green. When the confederates answered inconsistently about 1% of participants Said the slides were green.

A distinction can be made between two forms of consistency:

(a) Diachronic Consistency – i.e. consistency over time – the majority sticks to its guns, doesn’t modify its views. (b) Synchronic Consistency – i.e. consistency between its members – all members agree and back each other up.

Consistency may be important because:

1. Confronted with a consistent opposition, members of the majority will sit up, take notice, and rethink their position (i.e. the minority focuses attention on itself). 2. A consistent minority disrupts established norms and creates uncertainty, doubt and conflict. This can lead to the majority taking the minority view seriously. The majority will therefore be more likely to question their own views.

When the majority is confronted with someone with self-confidence and dedication to take a popular stand and refuses to back own, they may assume that he or she has a point.

Flexibility

A number of researchers have questioned whether consistency alone is sufficient for a minority to influence a majority. They argue that the key is how the majority interprets consistency. If the consistent minority are seen as inflexible, rigid, uncompromising and dogmatic, they will be unlikely to change the views of the majority.

However, if they appear flexible and compromising, they are likely to be seen as less extreme, as more moderate, cooperative and reasonable. As a result, they will have a better chance of changing majority views.

Some researchers have gone further and suggested that it is not just the appearance of flexibility and compromise which is important but actual flexibility and compromise. This possibility was investigated by Nemeth.

Their experiment was based on a mock jury in which groups of three participants and one confederate had to decide on the amount of compensation to be given to the victim of a ski-lift accident. When the consistent minority (the confederate) argued for a very low amount and refused to change his position, he had no effect on the majority.

However, when he compromised and moved some way towards the majority position, the majority also compromised and changed their view.

This experiment questions the importance of consistency. The minority position changed, it was not consistent, and it was this change that apparently resulted in minority influence.

(a) Name 3 behaviors that enable a minority to influence a majority. (3 marks)

(b) Marcus wants to persuade his group of friends to go travelling in the summer but the rest of the group would like to go on a beach holiday.

Briefly suggest how Marcus might use the 3 behaviors that you have identified in your answer to (a) to persuade his friends to go travelling. (3 marks)

(Total 6 Marks)

(a) Answer. “Consistency, Commitment, Flexibility.” (No need to explain – just name them). (b) Answer. “Marcus should consistently give the same message again and again that the group should go travelling rather than on a beach holiday. He should show commitment to his idea by, for example, investing time in planning and organising his proposed trip. Lastly, he should some flexibility: for example, he could suggest the group go travelling but they will spend quite a bit of time at the beach whilst travelling.”

Social Change

Social change occurs when a whole society adopts a new belief or behavior which then becomes widely accepted as the ‘norm’ which was not before. Social influence processes involved in social change include minority influence (consistency, commitment and flexibility), internal locus of control and disobedience to authority.

Social change is usually a result of minority influence . This is when a small group of people (the minority) manage to persuade the majority to adopt their point of view.

This also links to independent behavior, because the minority resists pressures to conform and/or obey. Usually the minority have an internal locus of control.

Committed minorities, such as those who risk themselves for their cause has an effect on the majority through an augmentation principle, this means the majority value the importance of the cause – as the minority are risking their lives for it.

Through these processes more and more of the majority will gradually change towards the cause resulting in the snowball effect which will ultimately result in societal change, once this has happened social cryptomnesia occurs which is when people can remember a change but not how it came about.

Moscovici found that consistency is the most important factor in deciding whether the minority are influential or not. This means that the minority must be clear on what they are asking for and not change their minds, or disagree amongst themselves. This creates uncertainty amongst the majority.

Moscovici investigated the importance of consistency. He had a group of 6 participants and a range of blue/ green slides varying in intensity – they all had to state the colour they saw.

The study had two conditions, confederates who consistently said green and an inconsistent group and a control group with no confederates. He found that the consistent minority group had a greater effect on the other participants than the inconsistent group. This confirms that consistency is a major factor in minority influence.

It has been found that once the minority begin to persuade people round to their way of thinking, a snowball effect begins to happen. This means that more and more people adopt the minority opinion, until gradually the minority becomes the majority.

At this point, the people who have not changed their opinion are the minority, and they will often conform to the majority view as a result of group pressures.

The majority opinion then becomes law, and people have to obey this law. Once this happens, the minority opinion has become the dominant position in society, and people do often not even remember where the opinion originated from. This is a process known as crypto amnesia .

Further social influence research from Asch and Milgram demonstrates that a minority can have an affect on the majority – both studies involved a dissenter or disobedient role model who influenced the behavior of the majority. However, there are methodological issues in these areas of research: these studies are both based on artificial tasks (judging line lengths).

The application of minority influence is further limited due to the importance of identification which is overlooked in minority influence research. Psychologists have suggested that people are less likely to behave in environmentally friendly ways due to the negative connotations associated with them (“tree huggers”).

Minorities wanting social change should avoid behaviors that reinforce social change – essentially off-putting to the majority.

This suggests that being able to identify with a minority group is just as important as agreeing with their views in order to change the behavior of the major.

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Table of Contents

I. introduction.

Picture this: you’re walking through a busy shopping mall when suddenly, a group of people around you starts clapping and cheering. Without even realizing it, you find yourself joining in, swept up by the contagious energy of the crowd. This seemingly innocuous example demonstrates the pervasive and powerful nature of social influence in our everyday lives. From the clothes we wear to the opinions we hold, it shapes our decisions and behaviors in countless ways.

In this increasingly interconnected world, social influence extends far beyond face-to-face interactions, reaching us through the screens of our smartphones and computers. Understanding the mechanisms behind social influence is crucial for navigating the complex web of influences that impact our lives, both online and offline.

In this article, we will delve into the fascinating world of social influence. We’ll explore the psychology that drives it, the factors that impact its strength, and the ways in which it manifests in the digital age. Furthermore, we’ll offer tips and strategies for developing critical thinking and self-awareness to better navigate the powerful currents of social influence.

II. The Psychology of Social Influence

A. Terminology

Social influence definition.

It’s all about the sway that the thoughts, actions, and feelings of others have on us. It’s that invisible force that nudges us to follow the crowd, pick up on trends, or give in to peer pressure. In a nutshell, it is how the people around us shape our decisions and behavior, whether we realize it or not.

Social Influence Meaning

Peeling back the layers of social influence, we find that it’s more than just a matter of following the leader. It encompasses a wide range of phenomena, from the subtle art of persuasion to the outright coercion of obedience. Its essence lies in our innate desire for social harmony, approval, and connection, which drives us to adapt our behavior, choices, and beliefs to fit in with those around us.

Social Influence Model

One way to make sense of social influence is through the lens of the social impact theory, a model that breaks it down into three key factors: strength, immediacy, and number. In a nutshell, this model suggests that the more powerful, close, and numerous the sources of influence, the more likely we are to be swayed by them. By understanding this dynamic interplay, we can better predict how social influence will unfold in various situations and empower ourselves to navigate its complexities with greater ease.

B. Social Influence Psychology

To better understand the psychology of social influence, let’s delve deeper into the three main types that govern our behavior:

Conformity occurs when we adjust our behavior or opinions to align with the norms or expectations of a group. This can happen consciously or unconsciously and is often driven by our innate desire for social acceptance and harmony. For example, you might adopt a specific fashion style to fit in with your friends or change your opinion on a controversial topic to avoid conflict within your social circle.

Compliance is the act of going along with a request or demand from others, even if we don’t necessarily agree with it. This is typically motivated by a desire to avoid negative consequences, such as rejection or punishment. An example of compliance could be agreeing to work overtime because your boss asked you to, even though you would rather not.

Obedience refers to the act of obeying an authority figure, even if it goes against our values or beliefs. This type of social influence is particularly powerful because we are often taught from a young age to respect and obey those in positions of authority. A classic example of obedience is following a law that we personally disagree with because of the potential consequences of disobedience.

C. Social Influence Theory

Several psychological theories help explain our susceptibility to social influence:

Social Identity Theory

We derive a sense of self and belonging from the groups we identify with, such as our family, friends, or professional peers. This identification drives us to adopt the values, attitudes, and behaviors of these groups, leading to conforming behaviors. The stronger our attachment to a group, the more likely we are to conform to its norms.

Normative Social Influence

It stems from our desire to be liked and accepted by others. In order to gain approval and avoid social disapproval or exclusion, we may conform to the expectations of those around us. This type of influence can be especially powerful in situations where we are uncertain about the appropriate behavior or where the group’s opinion is unanimous.

Informational Social Influence

It occurs when we look to others for guidance in situations where we lack knowledge or are uncertain about the correct course of action. We may conform to the behavior of others because we believe they possess more information or expertise than we do. This type of influence can lead to the spread of both accurate and inaccurate information within social networks.

D. Social Influence Examples

The psychology of social influence has been extensively studied, with numerous experiments and real-life examples shedding light on its power and mechanisms:

Asch Line Experiment

In this groundbreaking study conducted by Solomon Asch, participants were asked to judge the length of lines in a group setting. When other group members (who were actually confederates) unanimously chose the incorrect answer, the majority of participants conformed to the group’s opinion, even though the correct answer was clearly evident.

Milgram’s Obedience Experiment

Psychologist Stanley Milgram’s controversial study examined the extent to which people would obey an authority figure instructing them to administer increasingly painful electric shocks to another person. Despite the apparent distress of the “victim” (who was actually an actor), many participants continued to follow orders, demonstrating the powerful influence of authority on obedience.

Stanford Prison Experiment

In this infamous study led by Philip Zimbardo, college students were randomly assigned to play the roles of prisoners and guards in a simulated prison environment. The “guards” quickly began to exhibit abusive behavior, while the “prisoners” became passive and submissive. The experiment was terminated early due to the extreme psychological effects on the participants, illustrating the profound impact of social roles and expectations on behavior and conformity.

Bystander Effect

The bystander effect is a social phenomenon in which individuals are less likely to offer help to a victim when there are other people present. This can be attributed to a diffusion of responsibility, where each person assumes someone else will take action, as well as a reliance on the inaction of others as a cue for appropriate behavior. The tragic case of Kitty Genovese, who was assaulted and murdered while numerous witnesses failed to intervene or call for help, brought attention to this phenomenon and led to further research on the topic.

Social influence is shaping our behavior and decisions, often in ways that we may not be consciously aware of.

III. Factors That Impact Social Influence

It is not a one-size-fits-all phenomenon. Its strength and impact can be influenced by various factors, including group dynamics, personal factors, and the presence of authority figures or perceived expertise. Understanding these factors can help us recognize and mitigate the effects of social influence in our own lives.

A. Group Dynamics

The dynamics of a group can play a significant role in the strength of social influence:

• Group Size: Research has shown that as the number of people in a group increases, the likelihood of conforming grows. However, this effect plateaus once the group reaches a certain size, as the pressure to conform becomes diluted among the larger number of individuals.
• Group Cohesiveness: The more cohesive a group is, the stronger the pressure to conform. Cohesive groups often share similar values, beliefs, or goals, which can create a powerful sense of unity and identity. This can make it especially difficult to resist conforming to the group’s norms or expectations.
• Group Unanimity: When a group’s opinion is unanimous, the pressure to conform can be extremely strong. This is particularly true when the individual is uncertain about the correct course of action or when the group’s opinion is perceived as carrying significant weight or importance.

B. Personal Factors

Individual personality traits and cultural backgrounds can also influence our susceptibility to social influence:

• Personality Traits: Certain personality traits, such as conscientiousness, agreeableness, or a high need for social approval, may predispose individuals to be more prone to conforming behavior. Conversely, people with traits such as high self-esteem or independence may be less likely to conform.
• Cultural Background: Culture can play a significant role in shaping our susceptibility to social influence. Collectivist cultures, which prioritize group harmony and interdependence, may encourage greater conformity than individualistic cultures, which emphasize personal autonomy and self-expression.

C. Authority Figures and Expertise

The presence of authority figures or perceived expertise can amplify its power. We are more likely to conform to the opinions or demands of those we perceive as authority figures or experts in a particular field because we trust their judgment and may fear the consequences of disobeying them. This can be seen in cases like the Milgram experiment, where participants obeyed the experimenter’s orders despite their own moral reservations.

IV. Five Great Examples of Social Influence for a Better World

Dove’s Real Beauty Campaign

Dove’s Real Beauty campaign revolutionized the beauty industry by challenging traditional beauty standards and promoting body positivity. Through advertisements featuring women of diverse shapes, sizes, and ethnicities, Dove successfully used social influence to shift the public’s perception of beauty and inspire millions of women to embrace their natural appearance. The campaign’s impact on the industry has been long-lasting, leading many other brands to adopt more inclusive marketing strategies.

The Ice Bucket Challenge

The Ice Bucket Challenge was a viral social media campaign that raised awareness and funds for Amyotrophic Lateral Sclerosis (ALS) research. The challenge involved people dumping a bucket of ice water over their heads and nominating others to do the same, spreading rapidly across social media platforms. The power of social influence led millions of people to participate, raising over $115 million for ALS research and significantly accelerating the development of new treatments.

Malala Yousafzai’s Global Impact

Malala Yousafzai , a Pakistani activist for female education and the youngest Nobel Prize laureate, has used social influence to promote the importance of education for girls worldwide. After surviving a Taliban assassination attempt, Malala shared her story with the world, inspiring millions to support her cause. Through her advocacy, Malala has successfully influenced global policies and increased funding for girls’ education, improving the lives of countless young women.

Movember Foundation’s Men’s Health Campaign

The Movember Foundation is a global charity that uses social influence to raise awareness and funds for men’s health issues, including prostate cancer, testicular cancer, and mental health. The annual Movember campaign encourages men to grow mustaches during November and raise funds through their networks, effectively utilizing it to create a sense of community and drive positive change. Since its inception, the Movember Foundation has raised over $1 billion and funded more than 1,250 men’s health projects worldwide.

The #MeToo Movement

The #MeToo movement, founded by Tarana Burke and popularized by actress Alyssa Milano, has used the power of social influence to raise awareness about sexual harassment and assault. Through the simple act of sharing personal stories with the hashtag #MeToo, millions of survivors found solidarity and support. The movement has had a profound impact on society, leading to increased accountability for perpetrators, widespread discussions about consent and power dynamics, and significant legal reforms to protect survivors’ rights.

V. Social Influence in the Digital Age

The digital age has brought about a new era of social influence, where interactions and information dissemination take place at lightning speed across the globe. From social media platforms to online forums, the internet has amplified the power of social influence and introduced new dynamics to the way we conform, comply, and obey.

A. The Amplification of Social Influence

The internet has revolutionized the way we communicate, making it easier than ever to share ideas, opinions, and information with vast networks of people. This has given rise to new forms of social influence that are more far-reaching and pervasive than traditional face-to-face interactions:

• Rapid Information Spread: Digital platforms enable information to spread rapidly, allowing trends, beliefs, and opinions to gain traction quickly and reach large audiences. This can create a sense of urgency and importance around a particular issue or idea, making it more difficult to resist conforming.
• Peer Pressure and Social Comparison: Social media platforms create an environment where we are constantly exposed to the lives and opinions of others. This can lead to increased feelings of peer pressure and social comparison, as we strive to keep up with the ever-changing trends and standards presented online.

B. Viral Trends, Social Media Influencers, and Echo Chambers

The digital age has given rise to new forms of social influence that are unique to the online world:

• Viral Trends: The internet has the ability to turn obscure ideas or behaviors into viral trends that spread like wildfire. These trends can create intense pressure to conform, as people feel the need to participate in order to fit in or gain social approval.
• Social Media Influencers: Social media influencers are individuals who have amassed large followings on platforms like Instagram, YouTube, and TikTok. They hold significant sway over their followers, shaping their preferences, opinions, and behaviors. By endorsing products, promoting lifestyles, or sharing their opinions on various topics, influencers exert a powerful form of social influence on their audiences.
• Echo Chambers: Online platforms can create echo chambers, where individuals are exposed primarily to information and opinions that reinforce their existing beliefs. This can lead to a narrowing of perspectives and increased polarization, as people are less likely to encounter or engage with opposing viewpoints.

C. The Good, the Bad, and the Ugly

Social influence in the digital age is a double-edged sword, with both positive and negative implications:

• Positive Effects: The internet can be a powerful tool for inspiring positive change and mobilizing support for important causes. For example, social media campaigns can raise awareness of environmental issues, promote body positivity, or encourage mental health discussions. In these cases, digital social influence can drive progress and create a sense of unity around shared values.
• Negative Effects: On the other hand, the digital age has also given rise to more harmful forms of social influence. These include the spread of misinformation, the rise of cancel culture, and the promotion of unrealistic beauty or lifestyle standards. Additionally, the constant exposure to online opinions and trends can erode our critical thinking skills and make it more challenging to resist conforming to societal pressures.

VI. Tips for Critical Thinking and Self-Awareness

To better navigate the complex world of social influence, both online and offline, it’s essential to develop critical thinking skills and cultivate self-awareness. Here are some strategies and tips to help you recognize and manage the impact of social influence on your life:

A. Recognizing and Resisting Negative Social Influences

Being able to identify and resist negative social influences is crucial for maintaining a sense of autonomy and authenticity. Consider these strategies:

• Develop Critical Thinking Skills: Train yourself to question what you see, hear, and read. Analyze the source of the information, consider alternative viewpoints, and don’t be afraid to challenge the status quo. This will help you to better evaluate the credibility and validity of the information and opinions you encounter.
• Seek Diverse Perspectives: Deliberately expose yourself to a variety of sources and opinions, even those that challenge your own beliefs. This can help you to develop a more well-rounded understanding of issues and become more open to new ideas.
• Foster Self-Awareness: Reflect on your own values, beliefs, and motivations, and strive to make choices that align with your authentic self. By understanding what is truly important to you, you can better resist the pull of external influences and make more informed decisions.

B. Harnessing Positive Social Influence

Social influence can also be a force for good, driving positive change and personal growth. Here are some tips for leveraging positive social influence:

• Seek Out Positive Role Models: Surround yourself with individuals who inspire you to grow, learn, and improve. By learning from their experiences and emulating their positive qualities, you can harness the power of social influence for your own personal development.
• Use Social Influence to Drive Positive Change: Recognize the power of your own influence, and use it to promote constructive ideas, behaviors, and initiatives. Whether it’s championing an important cause, raising awareness about an issue, or supporting a friend in need, you can make a difference by leveraging the power of social influence in a positive way.

C. Reflecting on Your Experiences

Regularly reflecting on your experiences with social influence can help you to develop a deeper understanding of its impact on your life and choices:

• Identify Instances of Social Influence: Take the time to examine your choices and behaviors, and consider the extent to which they have been shaped by external influences. This can help you to develop a greater awareness of your susceptibility to social influence and identify areas where you may need to strengthen your critical thinking or self-awareness.
• Learn from Your Experiences: Use your reflections as an opportunity for growth and learning. By recognizing the ways in which social influence has shaped your life, both positively and negatively, you can make more informed decisions and take steps to better navigate the complex world of social influence in the future.

VII. The Future of Social Influence

As society continues to evolve and technology advances, the dynamics of social influence are also likely to change. While it is impossible to predict the future with certainty, we can identify some emerging trends and consider their potential impact on the way we experience and navigate social influence in the years to come.

A. The Growing Role of Artificial Intelligence

As artificial intelligence (AI) becomes increasingly integrated into our daily lives, it is likely to play a more significant role in shaping social influence:

• AI-driven Recommendations: AI algorithms are already being used by social media platforms and search engines to curate personalized content for users. As these algorithms become more sophisticated, they may wield even greater influence over the information we consume and the opinions we form.
• Virtual Influencers: The rise of virtual influencers—AI-generated or digitally designed personalities with large online followings—may also impact the dynamics of social influence. As these virtual figures gain popularity, their creators will be able to leverage their influence to shape public opinion and consumer behavior.

B. The Impact of Virtual Reality and Augmented Reality

Advancements in virtual reality (VR) and augmented reality (AR) technologies may also reshape the landscape of social influence:

• Immersive Social Experiences: As VR and AR technologies become more widely adopted, they could provide even more immersive social experiences, amplifying the power of social influence in these virtual environments.
• Blurring the Lines Between Reality and Virtual Worlds: The integration of VR and AR into our daily lives could blur the lines between the real and the virtual, potentially leading to new forms of social influence that are more difficult to recognize and resist.

C. Changing Social Dynamics

The future of social influence will also be shaped by broader societal shifts and changing social dynamics:

• Global Connectivity: As the world becomes more interconnected through technology and globalization, we may be increasingly exposed to diverse perspectives and cultures. This could both broaden our horizons and introduce new sources of social influence into our lives.
• The Fight Against Misinformation: Growing awareness of the prevalence and impact of misinformation may lead to a greater emphasis on media literacy and critical thinking education, helping individuals better navigate and resist the negative aspects of social influence.

D. Ethical Considerations and Regulation

As our understanding of social influence deepens and technology continues to evolve, we may see greater emphasis on ethical considerations and the potential need for regulation:

• Transparency and Accountability: There may be a growing demand for transparency and accountability in the way social media platforms and AI algorithms shape our online experiences, to ensure that they do not unduly manipulate our opinions and behavior.
• Regulation and Legislation: Governments and regulatory bodies may also become more involved in addressing the potential negative consequences of social influence in the digital age, implementing policies and guidelines to protect individuals from undue manipulation and coercion.

VIII. Conclusion

Social influence is an undeniable force that shapes our behavior, decisions, and beliefs throughout our lives. From the psychological underpinnings of conformity, compliance, and obedience to its increasingly complex dynamics in the digital age, our understanding of this phenomenon continues to evolve. As we look towards the future, advancements in technology, such as artificial intelligence, virtual reality, and augmented reality, as well as shifting social dynamics and ethical considerations, will further impact the ways in which social influence manifests itself in our lives.

To navigate this ever-changing landscape, it is crucial that we cultivate critical thinking skills, self-awareness, and a willingness to seek diverse perspectives. By actively reflecting on our experiences, we can better recognize and resist negative influences while harnessing the power of positive social influence for personal growth and positive change.

Ultimately, understanding and managing social influence requires a balance between adaptability and autonomy, openness to new ideas and trust in our own judgment. As we continue to explore the complexities of social influence, we can empower ourselves to lead more authentic and fulfilling lives, driven by a genuine understanding of our values and beliefs. By doing so, we not only strengthen our individuality but also contribute to a more informed, resilient, and diverse society, where the power of social influence can be harnessed for the greater good.

KEY CONCEPTS

What is social influence.

Social influence refers to the way our behavior, decisions, and beliefs are shaped by the presence or actions of others.

What are the three main types of social influence?

Conformity, compliance, and obedience are the three main types of social influence.

How has the digital age impacted social influence?

The digital age has amplified social influence through rapid information spread, peer pressure, and social comparison.

Who are social media influencers?

Social media influencers are individuals with large online followings who shape their audience’s preferences, opinions, and behaviors.

What are echo chambers?

Echo chambers are online spaces where individuals are primarily exposed to information and opinions that reinforce their existing beliefs.

How can I develop critical thinking skills?

Question what you see, analyze the source of information, consider alternative viewpoints, and challenge the status quo.

What role will AI play in the future of social influence?

AI will play a growing role in shaping social influence through AI-driven recommendations and the rise of virtual influencers.

How will virtual reality and augmented reality impact social influence?

VR and AR technologies may create more immersive social experiences, amplifying the power of social influence in virtual environments.

How can I resist negative social influences?

Develop critical thinking skills, seek diverse perspectives, and foster self-awareness to recognize and resist negative social influences.

How can I harness positive social influence?

Seek out positive role models, use social influence to drive positive change, and regularly reflect on your experiences with social influence.

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Social Influences on Behavior Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Social influences are things that alter or influence an individual’s feelings, conduct, opinions, or actions. Both sociologists and psychologists find this concept of great value, for example, social influence is a pivotal tool for marketing, smoking and many more.

Among the very many things under focus when handling the concept of social influence is how external factors affect behavior of certain faction or discrete individuals. In other words, nobody is exclusive of social influence as it can occur in any social condition. For instance, let us take prejudice, attraction and love as examples of social influences. It is quite apparent that prejudice develops feelings of misery or hate.

On the other hand, love and attraction brings feelings that an individual can help one up. Whether positive or negative, these conditions can light a rollercoaster ride in the brain and make an individual change from being irate to blissful or from cheerful to fuming, within a split second. Thus, undoubtedly, love and prejudice remains two paramount circumstances that induce sturdy feelings in humans-the chieftains of human behavior in society (Ainette & Carmella, 2011, p.1).

According to Kowalski and Westen (2009), schemas are the vital blueprint of thoughts, which systematize experience and direct the processing of information about human beings and situation. They go on saying that for this to occur, an impression of a person is necessary before anything else. Their work shows people that develop the first impression by observing the behavior of outgoing and attractive individuals.

Thus, if a person appears shy and reticent, the observer will have a shoddier first impression. In short, the first impression, either good or bad, forms the source of social behaviors. For instance, prejudice can make people behave imperfectly bearing in mind many people do not like the idea of becoming outcasts due to stereotype. It is thus important to note that the first impressions are the antecedent from where love and prejudice emanate.

Ordinarily, prejudice comes when a certain faction of people discriminate an individual either by race or color. Interestingly, the group has a leader who forces others to believe in discrimination. Although some members may be aware that what they are doing is wrong, they find themselves in a sorry state, as any resistance to what the group believes will makes them outcasts. Additionally, it is important to note that the group has an influencing power to facilitate socially how every member conducts himself or herself.

At the same time, no member of the group risks being an outcast by opposing others. Such cases are more common in children as compared to adults. As Kowalski and Westen notes, no substantive amount of salutary intercession can stop people from practicing prejudice and stereotyping. This is because many people follow the crowd irrespective of whether he crowd is doing the right thing or not. Perhaps this is the reason why in the contemporary world; altruism is something hard to come across (pp. 8-27).

Another component of social influence is the sensation of attraction and falling in love. The two, love and attraction, can develop as a first impression, in this case, directed towards a certain individual.

Noticeably, the foremost thing that a person keenly observes in a person of the opposite sex is of course, the physical appearance of that individual. Depending on personal preferences and even culture, each person has different assertions on the characteristics that attract him or her most. Nevertheless, it is important to note that at first sight, the first impression about someone is the paramount thing.

Any behavior of the sensation of attraction or love towards someone comes later. Undoubtedly, social researchers quickly assert that love is brings out the feeling of contentment and self-assurance in human beings. In most cases, where love exists, altruism comes into action, since the persons involved ends up being happy and better than they were (Schueler, 1997, p.1).

Studies show that love as complex as it is, exhibits itself as evolutionary and biological. In most cases, the studies explain the genesis of love as biological. However, it is important to note that due to social interactions, social groupings, social loafing and groupthink; the nature of love has made it easier to modify it into an assortment of cultures.

On the other hand, love exhibits itself when human beings protect their progeny. Nevertheless, some instances can make love plummet amid its disassociation from intervention of any type. For example, if one person becomes abusive due to stress or jealousy, then the concept of love as an ingredient of social influence ceases.

Captivatingly, some people may choose to remain in an abusive relationship just because they love their partners. Apparently, such situations require a certain therapy to deal with. In other words, love and prejudice are paramount circumstances that we cannot do without, simply because each one of them tries to accomplish various genuses of biological and evolutionary demands. For instance, prejudice pleads for inclusivity in major social groupings.

On the other hand, no human being likes being alone. All human being desires to associate with other people hence, the concept of love. It is also important to note that love is a fundamental necessitate for reproduction and survival. Perhaps this is the reason why people appear to care for others and making sure that the lineage survives (Kowalski & Westen, 2009, pp. 31-76).

In conclusion, so far, love and prejudice remain the strongest social influences on how human beings conduct themselves. From the two emanate an assortment of motions that range from irritation to hopelessness to self-assurance and happiness. Without any doubt, the behavior of people can affect the attitude and self-esteem of other people in social loafing. Social influence can also affect individual personality and behavior, and sometimes lead to discrimination.

Reference List

Ainette, M. & Carmella, W. (2011). Social Influence. Behavioral Research . Web.

Kowalski, R., & Westen, D. (2009). Psychology . (5th ed.). Hoboken, New Jersey: Wiley and Sons.

Schueler, G. (1997). Social Influence on Behavior. Web.

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Social influence on positive youth development: A developmental neuroscience perspective

Susceptibility to social influence is associated with a host of negative outcomes during adolescence. However, emerging evidence implicates the role of peers and parents in adolescents’ positive and adaptive adjustment. Hence, in this chapter we highlight social influence as an opportunity for promoting social adjustment, which can redirect negative trajectories and help adolescents thrive. We discuss influential models about the processes underlying social influence, with a particular emphasis on internalizing social norms, embedded in social learning and social identity theory. We link this behavioral work to developmental social neuroscience research, rooted in neurobiological models of decision-making and social cognition. Work from this perspective suggests that the adolescent brain is highly malleable and particularly oriented towards the social world, which may account for heightened susceptibility to social influences during this developmental period. Functional magnetic resonance imaging (fMRI) has been used to investigate the neural processes underlying social influence from peers and family as they relate to positive, adaptive outcomes in adolescence. Regions of the brain involved in social cognition, cognitive control, and reward processing are implicated in social influence. This chapter underscores the need to leverage social influences during adolescence, even beyond the family and peer context, to promote positive developmental outcomes. By further probing the underlying neural mechanisms as an additional layer to examining social influence on positive youth development, we will be able to gain traction on our understanding of this complex phenomenon.

I. A developmental social neuroscience perspective on social influence

If your friends jumped off a cliff, would you too? Everyone has heard this phrase at some point in their lives, either in the position of a worried parent or not-so-worried teenager. Indeed, a vast literature indicates that health-compromising risky behaviors increase when adolescents are with their peers (reviewed in Van Hoorn, Fuligni, Crone, & Galván, 2016 ). Emerging evidence from developmental neuroscience suggests that the adolescent brain is highly plastic and undergoes a major “social reorientation” ( Nelson, Leibenluft, McClure, & Pine, 2005 ), which may render adolescents particularly susceptible to social influences. While the focus of most research, popular media, and parental worries has been directed towards seeing social influence susceptibility as negative, leading teens to engage in dangerous behaviors, recent attention has sought to understand how adolescents’ heightened social influence susceptibility may be redirected towards positive, adaptive behaviors.

In this chapter, we review emerging evidence highlighting how social influences from both peers and family can play a positive role in adolescents’ adjustment. We first define social influence, focusing on two influential theories, social learning theory and social identity theory, both of which discuss social influence in terms of internalizing group norms. We then review literature highlighting several sources of social influence, including dyadic friendships, cliques, social networks, parents, siblings, and the larger family unit. Given the important neural changes occurring in adolescence, we describe the important role of maturational changes in the developing brain that may underlie susceptibility to social influence. We discuss prominent models of adolescent brain development and then review emerging research highlighting how family and peer influence are represented at the neural level. Finally, we conclude with future directions underscoring the need to capitalize on social influences from peers and parents during adolescence, examine different sources of social influence in the context of the larger social network, and expand our knowledge on the neural mechanisms underlying social influence.

II. Defining Social Influence

What is social influence? At the most basic level, social influence “comprises the processes whereby people directly or indirectly influence the thoughts, feelings, and actions of others” ( Turner, 1991 , pg. 1). When most people think of social influence, images of peers cheering on their friends to drink, do drugs, or engage in risky and reckless behavior likely come to mind. Popular misconceptions about social influence that saturate the media and parents’ worries too often focus on these very explicit, overt, and negative examples. But what many do not realize is that social influence is much more subtle and complex, and cannot often be identified so easily. In fact, direct peer pressure is not associated with adolescents’ smoking intentions, whereas the perceived behaviors of peers are ( Vitoria, et al., 2009 ). Moreover, social influence has many positive implications, for instance, exposing youth to positive social norms such as school engagement, cooperating with peers, donating money, and volunteering for a good cause. In this section, we will review prominent theories of social influence with a particular emphasis on the internalization of social norms, embedded in social learning and social identity theory.

A. Social Norms

A social norm is “a generally accepted way of thinking, feeling, or behaving that is endorsed and expected because it is perceived as the right and proper thing to do. It is a rule, value or standard shared by the members of a social group that prescribes appropriate, expected or desirable attitudes and conduct in matters relevant to the group” ( Turner, 1991 , pg. 3). Group norms are further defined as “regularities in attitudes and behavior that characterize a social group and differentiate it from other social groups” ( Hogg & Reid, 2006 , pg. 7). Norms are therefore shared thoughts, attitudes, and values, governing appropriate behavior by describing what one ought to do, and in essence prescribe moral obligations ( Cialdini & Trost, 1998 ). Social norms are communicated by what people do and say in their everyday lives, which can be indirect (e.g., inferring norms from others’ behaviors) but also direct (e.g., intentionally talking about what is and is not normative of the group; Hogg & Reid, 2006 ). Deviation from the social norms of a group can result in loss of social status or exclusion, particularly if the social norm is important to the group ( Festinger, 1950 ). Thus, norms serve to reinforce conformity by promoting the need for social acceptance and avoidance of social punishments (e.g., Deutsch & Gerard, 1955 ).

Social norms have a profound impact on influencing attitudes and behaviors, even though people are typically unaware of how influential social norms are ( Nolan et al., 2008 ). In fact, people are strongly influenced by social norms even when they explicitly reject such norms ( McDonald, Fielding, & Louis, 2013 ). In a classic study, Prentice and Miller (1993) asked Princeton undergraduates how comfortable they versus the average Princeton undergraduates are with drinking. Results across several studies converged on the same conclusion – individuals believe others are more comfortable with drinking than themselves. This phenomenon is referred to as pluralistic ignorance (e.g., Prentice & Miller, 1996 ), which occurs when people personally reject a group norm, yet they incorrectly believe that everyone else in the group engages in the behavior. This introduces a “perceptual paradox” – in reality the behavior is not the norm since nobody engages in it, yet it is the group norm because everyone thinks everyone else does engage in the behavior ( Hogg & Reid, 2006 ). Adolescents also misjudge the behaviors of their peers and close friends. Referred to as the false consensus effect, adolescents misperceive their peers’ attitudes and behaviors to be more similar to their own or even overestimate their peers’ engagement in health-risk behaviors ( Prinstein & Wang, 2005 ). Thus, adolescents overestimate the prevalence of their peers’ behaviors and use their (mis)perceptions of social norms as a standard by which to compare their own behavior.

B. Social Learning Theory

Social learning theory provides the basis for how social norms are learned and internalized during adolescence. Although this theory was originally developed to describe criminality and deviant behavior, its propositions can also be applied to positive social learning. Akers ( 1979 , 2001 , 2011 ) identified four core constructs of social learning: differential association, differential reinforcement, imitation or modeling, and definitions . Differential association refers to the direct association with groups who express certain norms, values, and attitudes. The groups with whom one is associated provides the social context in which all social learning occurs. The most important groups include family and friends, but can also include more secondary sources such as the media ( Akers & Jensen, 2006 ). According to Sutherland’s differential association theory ( Sutherland, Cressey, & Luckenbill, 1992 ), learning takes place according to the frequency, duration, priority, and intensity of adolescents’ social interactions. Adolescents will learn from and internalize social norms if (1) associations occur earlier in development (priority), (2) they associate frequently with others who engage in the behavior (frequency), (3) interactions occur over a long period of time (duration), and (4) interactions involve individuals with whom one is close (e.g., friends and family) as opposed to more casual or superficial interactions (intensity). The more one’s patterns of differential association are balanced towards exposure to prosocial, positive behavior and attitudes, the greater the probability that one will also engage in positive behaviors. Association with groups provides the social context in which exposure to differential reinforcement, imitation of models, and definitions for behaviors take place ( Akers, 1979 ).

Differential reinforcement refers to the balance of past, present, and anticipated future rewards and punishments for a given behavior ( Akers & Jensen, 2006 ), and includes the reactions and sanctions of all important social groups, especially those of peers and family, but can also include other groups such as schools and churches ( Akers, 1979 ; Krohn et al., 1985 ). In particular, behaviors are strengthened through rewards (i.e., positive reinforcement; e.g., peer acceptance of behaviors) and avoidance of punishments (i.e., negative reinforcement; e.g., peer rejection of behaviors) or weakened though receiving punishments (i.e., positive punishment; e.g., being grounded by parents) and loss of rewards (i.e., negative punishment; e.g., having the family car taken away; Akers, 1979 ). Behaviors that are reinforced, either through social rewards or the avoidance of social punishments, are more likely to be repeated, whereas behaviors that elicit social punishments are less likely to be repeated ( Akers, 2001 ). Thus, through differential reinforcement, individuals are conditioned to internalize the social norms that are valued by the group.

Social behavior is also shaped by imitating or modeling others’ behavior. Individuals learn behaviors by observing those around them ( Bandura, 1977 , 1986 ), particularly close others such as parents, siblings, or friends. The magnitude of social learning, and imitation in particular, is strengthened the more similar the individuals are ( Bandura, 1986 , 2001 ). Social influence has an effect on youth when adolescents are exposed to the behaviors and norms of others (i.e., mere exposure) and observe the positive outcomes others receive from such behaviors (i.e., vicarious learning). Adolescents then internalize such social norms and model the behaviors in future instances.

Finally, definitions are the attitudes, rationalizations, or meanings that one attaches to a given behavior that define the behavior as good or bad, right or wrong, justified or unjustified, appropriate or inappropriate ( Akers & Jensen, 2006 ). The more individuals have learned that specific attitudes or behaviors are good or desirable (positive definition) or as justified (neutralizing definition) rather than as undesirable (negative definition), the more likely they are to engage in the behavior ( Akers, 1979 ). These definitions are learned through imitation and subsequent differential reinforcement by members of their peer and family groups. Although there may be norm conflict in terms of the definitions promoted by one’s peers (e.g., positive definition for alcohol) and parents (e.g., negative definition for alcohol), the relative weight of such definitions will determine whether an adolescent endorses the social norm and engages in the behavior. An individual will engage in the behavior when the positive and neutralizing definitions of the behavior offset the negative definitions ( Akers, 1979 ).

C. Social Identity Theory

Group identification is essential for understanding the effects of social norms ( Turner, 1991 ). According to social identity theory, social influence occurs when individuals internalize contextually salient group norms, which set the stage for their self-definition, attitudes, and behavioral regulation ( Tajfel, 1981 ; Tajfel & Turner, 1979 ; Hogg & Reid, 2006 ). From a social identity perspective, norms reflect a shared group prototype, which are individuals’ cognitive representations of group norms ( Hogg & Reid, 2006 ). Group prototypes describe normative behaviors and prescribe behavior, indicating how one ought to behave as a group member. Thus, strong group identification can lead to social influence and conformity because individuals endorse the behaviors they should engage in based on the social norms prescribed by group prototypes ( Terry & Hogg, 1996 ).

The family is the first and primary social group to which most individuals belong ( Bahr et al., 2005 ), whereas friends become an increasingly salient social identity during adolescence, a developmental period marked by a need to belong and affiliate with peers ( Crockett et al., 1984 ; Newman & Newman, 2001 ; Kroger, 2000 ; Furman & Buhrmester, 1992 ; Hart & Fegley, 1995 ). Importantly, the social environment can activate certain identities and determine whether an individual will be influenced ( Oakes, 1987 ). Across development (e.g., from childhood to adolescence) and across contexts (e.g., at school versus at home), different social identities (e.g., family versus peers) will be more or less salient, affecting whether group norms are strongly internalized and activated.

Adolescents are not only influenced by a single salient group but also by the norms of multiple groups ( McDonald et al., 2013 ), including family, close friends, out-group peers, and the broader societal norms. When more than one social identity is activated, norm-conflict may occur, especially if there are inconsistencies across group norms ( McDonald et al., 2013 ). A particularly prominent example of this likely occurs in adolescents’ daily lives when the norms and valued behaviors of the peer group (e.g., drinking alcohol is fun) conflict with the norms internalized at home (e.g., drinking alcohol is unacceptable behavior). Although seemingly bad, norm conflict can potentially increase motivation to engage in a behavior, because the norm conflict reinforces the need to personally act ( McDonald et al., 2013 ). As an example, if a teen sees a peer being bullied at school, and her close friends are cheering on the bully to continue picking on the teen, but another group of her peers is expressing concern for the teen, an adolescent may be moved to act and stick up for the victim due to this conflict, because she sees the need to personally act. Thus, when multiple group identities are activated and norm-conflict occurs, teens may be motivated to engage in a positive behavior ( McDonald et al., 2013 ).

III. Social influence on positive youth development

Social learning and social identity theories highlight that a myriad of social influences affect positive adjustment during adolescence. Sources of social influence include peers, family, teachers, other attachment figures (e.g., coach of sports team, youth group leader) and even (social) media ( Akers 1979 ; Bandura, 2001 ; McDonald et al., 2013 ). In this chapter, we specifically focus on social influences from peers and family and their interactions, given the saliency of developmental changes in these social relationships during adolescence ( Bronfenbrenner & Morris, 2006 ). Although peers are often referred to as a unified construct (i.e., persons of the same age, status, or ability as another specified person) previous research has assessed a wide range of peers that fall under this umbrella. Hence, we make a distinction between best friend dyads, smaller peer groups such as cliques, and larger peer groups of unknown others. Family influences similarly encompass multiple layers, and here we review influences from parents, siblings and their interactions within the larger family unit. Finally, we will discuss literature that examines these social influences simultaneously.

A. Peer influence on positive adolescent development

Peer influence has predominantly negative connotations and received most attention in the context of problem behaviors during adolescence. Indeed, extant research has shown that hanging out with the wrong crowd may increase deviant behaviors through processes of social reinforcement or “peer contagion” (reviewed in Dishion & Tipsord, 2011 ). For example, in videotaped interactions between delinquent adolescent males, rule-breaking behaviors (e.g., mooning the camera, drug use, obscene gestures) were socially reinforced through laughter, and this was predictive of greater delinquent behavior two years later ( Dishion, Spracklen, Andrews, & Patterson, 1996 ). Importantly however, the very same social learning process reinforced normative and prosocial talk (e.g., non-rule breaking topics such as school, money, family and peer-related issues) in non-delinquent adolescent dyads. This highlights the benefits of hanging out with the right crowd, and shows that imitation and social reinforcement in the peer context can also shape positive development. This section provides an overview of behavioral research that has examined peer socialization of prosocial behaviors during adolescence, as well as the application of peer processes in interventions to promote positive adjustment outcomes.

Peer influence in close friendships.

Prosocial behavior is a broad and multidimensional construct that includes cooperation, donation, and volunteering ( Padilla-Walker & Carlo, 2014 ). Given the association between prosocial engagement during adolescence and a range of adult positive adjustment outcomes (e.g., mental health, self-esteem, and better peer relations; reviewed in Do, Guassi Moreira, & Telzer, 2017 ), it is crucial to understand how peers can promote these behaviors. There is consistent evidence that best friends influence prosocial behaviors. In adolescent best friend dyads, a friend’s prosocial behavior is related to an individual’s prosocial goal pursuit, which, in turn, is associated with an individual’s prosocial behavior (e.g., cooperating, sharing and helping) ( Barry & Wentzel, 2006 ). These effects are moderated by friendship characteristics, including friendship quality ( Barry & Wentzel, 2006 ) and closeness between friends ( Padilla-Walker, Fraser, Black, & Bean, 2015 ; see Brown, Bakken, Ameringer, & Mahon, 2008 for a comprehensive chapter on pathways of peer influence). In particular, a friend’s prosocial behavior is most likely to influence adolescent’s own prosocial behavior when there is a strong positive relationship and greater closeness between friends, consistent with Sutherland’s differential association theory ( Sutherland et al., 1992 ). Moreover, not only do actual behaviors , but also perceived peer expectations about positive behaviors in the classroom predict greater prosocial goal pursuit and subsequent sharing, cooperating, and helping ( Wentzel, Filisetti, & Looney, 2007 ). These results underscore that getting along with peers is a powerful social motive to behave in positive, prosocial ways. Together, this work suggests that social influence on prosocial behavior is likely explained by processes of social learning ( Bandura, 2001 ).

Peer influence in small groups.

Experimental techniques allow one to manipulate peer effects on prosocial behaviors to better understand the mechanisms of social influence. In one study, we employed a public goods game, in which participants allocated tokens between themselves and a group of peers ( Van Hoorn, Van Dijk, Meuwese, Rieffe, & Crone, 2016a ). After making decisions individually, participants were ostensibly observed by a group of ten online peer spectators, who provided either prosocial feedback (i.e., likes for donating to the group) or antisocial feedback (i.e., likes for selfish decisions) on their decisions. Adolescents changed their behavior in line with the norms of the spectator group and showed greater prosocial behavior after feedback from prosocial spectators, but became more selfish with antisocial spectators ( Van Hoorn et al., 2016a ). Results from this study were corroborated by other experimental work showing that peers also positively influence intentions to volunteer ( Choukas-Bradley, Giletta, Cohen, & Prinstein, 2015 ). Moreover, adolescents conformed more to high-status peers’ intentions to volunteer than low-status peers’ intentions to volunteer, suggesting that adolescents are more susceptible to salient peers, consistent with social identity theory ( Hogg & Reid, 2006 ). In sum, experimental studies show that social norms are influential in the domain of prosocial behaviors (cooperation and intentions to volunteer), and can serve both as a vulnerability and an opportunity in adolescent development.

Peer influence in social networks.

Finally, other research has utilized social network analysis to study peer effects in the context of the larger group and highlights that specific characteristics of the larger social group may mitigate or magnify peer effects. For example, findings from one study illustrate that highly central (i.e., high status in larger network, trend setters in school) social groups within the larger network endorsed prosocial as well as aggressive and deviant behaviors, whereas groups with lower centrality (i.e., groups with low acceptance in the larger network) showed magnified socialization of deviant behaviors only ( Ellis & Zabartany, 2007 ). Moreover, adolescents tend to shift between different social groups, and there is evidence for socialization of prosocial behaviors from the attracting social group (i.e., the group to be joined), but not the departing social group (i.e., the group left behind) ( Berger & Rodkin, 2012 ). These results suggest that although adolescent’s membership in different peer groups can influence their engagement in positive and negative behaviors, there is often flexibility in the peer groups adolescents choose to identify with. Thus, to fully grasp peer effects, it is important to study multiple levels of the peer context, taking into account the dynamics between dyads, groups, and the larger social network.

Practical implications of positive peer effects.

The studies reviewed above provide a promising foundation for interventions that employ peer processes in order to potentially increase positive behaviors, as well as redirect negative behaviors during adolescence. One intervention that has shown promising effects is the Good Behavior Game, which teamed up non-disruptive and disruptive children ( Van Lier, Huizink, & Vuijk, 2011 ). When one child reinforced positive and prosocial classroom behaviors, their entire team was rewarded, resulting in more positive peer relations and reduced rates of tobacco experimentation three years later. Another study aimed to redirect collective school norms concerning harassment and utilized social networks to identify social referents (e.g., widely known adolescents or leaders of subgroups) within the school network ( Paluck & Shepherd, 2012 ). They then successfully used these social referents within the school setting to change their peers’ perceptions of norms concerning harassment over the school year, which reduced peer victimization. Collectively, these interventions take advantage of peer processes to change social norms and subsequently promote positive psychosocial outcomes.

B. Family influence on positive adolescent development

A considerable portion of research on social influence during adolescence focuses on the growing effect of peer relations, while deemphasizing the role of the family during this developmental transition. However, characterizing social influence during adolescence is hardly this simple. The family context continues to impact the attitudes, decisions, and behaviors of adolescents, particularly in guiding them toward positive adjustment (e.g., Van Ryzin, Fosco, & Dishion, 2012 ). The family context is a dynamic system that constantly affects the way in which adolescents think, behave, and make decisions. The family systems model presents these processes as each family member having continuous and reciprocal influence on one another throughout development ( Cox & Paley, 1997 ; Minuchin, 1985 ). For example, the family context influences each family member’s expectations, needs, desires, and goals. And together, each individual contributes to the family culture, including allocation of resources as well as family rituals, boundaries, and communication ( Parke, 2004 ). To put it simply, the whole is greater than the sum of parts, and the family is no exception during adolescent development ( Cox & Paley, 1997 ). In this section, we review research on families as a salient context for positive adolescent development and provide examples of parents, siblings, and multiple family members together in contributing toward adolescent adjustment.

Parental influence.

The importance of parental influence on positive adolescent development has been well established using longitudinal studies with multiple-informant questionnaires. Many studies converge on the finding that parental management predicts adolescent psychosocial adjustment. Authoritative parenting, which is characterized by frequent involvement and supervision, is associated with higher levels of adolescent academic competence and orientation and lower delinquency compared to other parenting styles ( Steinberg et al., 1994 ). Specifically, parents who are involved in their child’s school life (e.g., attendance, open-house) and who engage in intellectual activities (e.g., reading, discussing current events) tend to have adolescents who display high academic competence and school achievement ( Grolnick & Slowiaczek, 1994 ). In addition to managing and being involved in the lives of adolescents, parent-child relationship quality also affects adolescent development. Adolescent perceptions of closeness and trust with their parents predict better academic competence, engagement, and achievement ( Murray, 2009 ), as well as decreases in depressive symptoms for girls ( Guassi Moreira & Telzer, 2015 ).

Another approach to investigating parental influence on adolescent development includes examining parental beliefs and behaviors specific to the domain of interest, such as verbally promoting academics or athletics, or buffering against risky sexual behavior. When mothers take interest in, or value a specific behavior, such as doing well in school, their adolescents are also more likely to take interest ( Dotterer, McHale, & Crouter, 2009 ), which is an example of attitude definitions in social learning theory ( Akers & Jensen, 2006 ). One study examined maternal influences on adolescent beliefs and behaviors in the domains of reading, math, art, and athletics across childhood and adolescence. Mothers who displayed relevant beliefs, such as valuing the domain and their child’s competence in the domain, as well as demonstrated relevant behaviors themselves, such as modeling and encouragement, had adolescents who valued and engaged more in each domain ( Simpkins, Fredricks, & Eccles, 2012 ). Collectively, these studies show the power of parental influence on adolescent development through involvement, closeness, and displaying positive beliefs and behaviors. Clearly, parents continue to impact their children’s decisions across adolescence through parental values and parent-child conversations about the adolescent’s friends, whereabouts, and daily lives.

Sibling influence.

Recently, there has been a surge in research examining sibling relationships due to their salient influence on adolescent health and well-being ( Conger, 2013 ). Sibling influences can be especially impactful during developmental transitions ( Cox, 2010 ), helping adolescents navigate new roles and adjust to social and physical changes ( Eccles, 1999 ). Siblings primarily influence each other through two mechanisms: social learning, which is the process of observing and selectively integrating modeled behaviors, and through deidentification, which is the process of actively behaving differently from one another ( Whiteman, Beccera, & Killoren, 2009 ). However, these mechanisms largely depend on one factor—perceptions of support (for a review see, Dirks, Persram, Recchia, & Howe, 2015 ).

Although research on sibling relationships has traditionally focused on conflict and rivalry as it contributes to negative child and adolescent outcomes, accumulating research suggests that siblings positively influence adolescent development through sibling relationships built upon support ( Conger, 2013 ). Adolescents who perceive general closeness and academic support from siblings are more likely to report positive school attitudes and high academic motivation ( Alfaro & Umaña-Taylor, 2010 ; Milevsky & Levitt, 2005 ). In addition, experiencing support from a sibling is associated with later feelings of competence, autonomy, and relatedness during adolescence, as well as life satisfaction during the transition into emerging adulthood ( Hollifield & Conger, 2015 ). Further, in the face of stressful life events, perceived affection and closeness from a sibling can buffer against the progression of internalizing behaviors across adolescence ( Buist et al., 2014 ; Gass, Jenkins, & Dunn, 2007 ). These are just a sample of studies that highlight how powerful sibling relationships can be in socializing adolescents toward prosocial behavior and maintaining well-being. Future work should tap into siblings as a natural resource to bolster positive adolescent development.

The influence of multiple family members.

Although we have reviewed literature examining one parent or one sibling, research has also investigated the combined influence of multiple family members, which reflects the essence of the family systems model ( Cox, 2010 ). Parental and sibling influences are intertwined in adolescent’s daily lives, and thus, are important to investigate together to better inform our understanding of positive adolescent development ( Tucker & Updegraff, 2009 ). Mothers, fathers, and siblings can all contribute to adolescent psychosocial adjustment by providing supervision, acceptance, and opportunities for autonomy ( Kurdek & Fine, 1995 ). For example, high levels of parental involvement and high levels of sibling companionship are associated with lower substance use during adolescence ( Samek, Rueter, Keyes, McGue, & Ianoco, 2015 ). In addition, both observed parental support, and sibling-reported sibling relationship quality, positively contribute to academic engagement during adolescence, and educational attainment in emerging adulthood ( Melby, Conger, Fang, Wickrama, & Conger, 2008 ). Parents and siblings can also work together to buffer adolescents against negative life events. One study found that for adolescent victims of bullying who also experienced low parental conflict and low sibling victimization, boys reported lower levels of depression and girls reported lower levels of delinquency compared to adolescents who experienced high dissatisfaction at home ( Sapouna & Wolke, 2013 ). Moreover, sometimes siblings can provide support when parents come up short. Older siblings can buffer the negative effect of hostile parental behaviors on adolescent externalizing behavior by providing younger siblings with a warm and supportive relationship ( Conger, Conger, & Elder, 1994 ). Together, these studies suggest that adolescent development is heavily influenced by the family context, and by each family member. The social susceptibility and flexibility present during adolescence allows teens to benefit from the influence of multiple family members, even when one source of family influence is compromised. Thus, both parents and siblings need to be examined together to better inform our understanding of how the family can positively influence adolescent decision-making and well-being, including both the nature of influence (e.g., support, involvement) and the degree to which the influence is present (e.g., absent versus helicopter parenting).

C. Family and peer influence on positive adolescent development

Despite extensive research examining how family and peers uniquely influence a wide range of adolescent behaviors, less is known about how these sources of influence simultaneously guide adolescent decision making in positive ways. Indeed, adolescents often face the need to reconcile potential differences in the attitudes and behaviors endorsed by their family relative to peers. Extant research examining social conformity across development supports the reference group theory ( Shibutani, 1955 ), which suggests that individuals adopt the perspectives of different social reference groups (e.g., family or peers) based on their perceived relevance in guiding that decision. Using this theoretical framework, we review literature examining the social contexts in which adolescents rely more on their family or peer influence when faced with conflicting information, which can, in turn, reinforce the development of positive social norms and relationships, as well as promote adaptive decision making.

Susceptibility to social conformity.

Susceptibility to parent versus peer pressures changes with age, resulting in different rates of social conformity across development. One of the earliest methods used to explore how family and peer influence interact and contribute to positive adolescent behaviors was cross-pressures tests, where adolescents respond to hypothetical situations in which their parent and/or peers suggest conflicting actions. From childhood to adolescence, there is a general increase in the tendency for youth to conform to the perspectives of their peers when parents and peers offer conflicting advice ( Utech & Hoving, 1969 ). This supports other work showing the social value of peers is also increasing with age ( Bandura & Kupers, 1964 ), suggesting that, relative to parents, peers may be more successful at reinforcing certain norms or behaviors across development. Consistent with social learning and social identity theories, these results suggest that over the course of adolescence, youth may be shifting their attitudes to align with whichever reference group (e.g., parents or peers) is more salient (i.e., social identity), whose norms may become differentially reinforced over time (i.e., social learning). However, distinct developmental trajectories emerge when adolescents are evaluating different types of behaviors. For example, one study examined parent and peer conformity to prosocial behaviors and found both parent and peer conformity to prosocial behaviors declined from childhood to adolescence (albeit results for peer conformity to prosocial behaviors are inconsistent) ( Berndt, 1979 ). The fact that youth are conforming to their parent or peer influence less often in considering prosocial actions illustrates their increasing ability to make positive decisions independently with age, without the need for a reference group. Not only do these findings suggest that youth seek guidance from parents or peers differently based on the type of behavior under consideration, but they also highlight childhood and early adolescence as an important developmental transition for promoting positive social influence, either by parents or peers.

Flexibility of norms and behaviors.

Evidence from qualitative interview studies demonstrates the flexibility and potential mechanisms by which interacting sources of social influence shape youth’s norms and behaviors. The degree to which parent or peer pressures impact adolescent decision making varies systematically across domains, such that adolescents are more likely to seek guidance about future- or career-oriented topics (e.g., applying for college) from parents and about status- or identity-related topics (e.g., attending social events) from peers ( Biddle, Bank, & Marlin, 1980 ; Brittain, 1963 ; Sebald & White, 1980 ). Interestingly, adolescents rely more heavily on parents’ advice when their choices are perceived to be more difficult, such as in situations involving ethical or legal concerns (e.g., reporting a peer’s crime; Brittain, 1963 ). Another study examined the relative impact of parent and peer norms (e.g., do your parents/peers think you should/shouldn’t do well in school?) versus behaviors (e.g., did your parents/peers do well in school?) on adolescents’ own norms and behaviors as it related to school achievement and alcohol use ( Biddle et al., 1980 ). Adolescents’ alcohol use was more strongly influenced by peers’ behaviors, whereas school achievement was more strongly influenced by parental norms ( Biddle et al., 1980 ). While adolescents can adapt to parent and peer pressures under the appropriate circumstances (e.g., different domains), the extent to which adolescents internalize those pressures—insofar that parent/peer pressures are adopted as adolescents’ own norms—may determine whether those pressures result in more positive or negative decisions.

Parents often influence their adolescents’ peer group affiliations, which also affects the strength and type of norms and behaviors that youth are exposed to. Positive parenting practices lead youth to engage in more adaptive behaviors (e.g., academic achievement), which, in turn, promote affiliation with better peer groups (e.g., “populars” over “druggies;” Brown, Mounts, Lamborn, & Steinberg, 1993 ). In fact, peer pressures are generally stronger within positive domains (e.g., school achievement) compared to negative domains (e.g., misconduct), especially among social groups that are well interconnected (i.e., less alienated) within the school structure ( Clasen & Brown, 1987 ). These studies highlight the significant role that parents can play in promoting prosocial peer affiliations, which may subsequently facilitate opportunities for peers to positively influence youth’s decision making.

Protective role of positive relationships.

In addition to promoting prosocial peer affiliations, positive social figures can buffer adolescents against negative social pressures over time. Positive family influence can attenuate the potentially negative impact of peers on adolescents’ well-being. Indeed, warm family relationships and environments promote resilience to peer bullying ( Bowes, Maughan, Caspi, Moffitt, & Arseneault, 2010 ) and mitigate the effect of peer pressure on alcohol use ( Nash, Mcqueen, & Bray, 2005 ) among youth. As peers become increasingly important across adolescence, positive peer influence can similarly protect against aversive family experiences. For example, family adversity (e.g., harsh discipline) is not associated with child externalizing behaviors for youth with high levels of positive peer relationships ( Criss, Pettit, Bates, Dodge, & Lapp, 2002 ). This highlights the potential of strong peer support in redirecting negative developmental trajectories, particularly among vulnerable youth.

In some cases, peers may serve as a stronger buffer against poor developmental outcomes than parents. One study examined how the perceived expectations of mothers and friends influenced adolescents’ engagement in antisocial and prosocial behaviors ( Padilla-Walker & Carlo, 2007 ). Adolescents indicated how strongly they personally agreed with the importance of engaging in several prosocial behaviors (e.g., helping people), as well as rated how much they felt their mother versus friends expected them to engage in these same prosocial behaviors. Adolescent boys who perceived their peers to have stronger expectations of their prosocial engagement actually participated in fewer antisocial behaviors; there was no effect of maternal expectations or personal values on their antisocial behaviors. Thus, positive peer influence may be more protective against antisocial behaviors for adolescent boys relative to girls. In contrast, both the perceived expectations of mothers and friends were related to adolescents’ personal prosocial values, which subsequently influenced their prosocial behaviors. Although peers may be a stronger protective factor against negative behaviors compared to family, adolescents rely on the social norms of both their family and peers to inform their own values and choices about engaging in more adaptive, positive behaviors (a la social identity theory). In the following sections, we review prominent neurobiological theories, which describe how heightened social influence susceptibility during adolescence may reflect maturational changes in how the brain responds to social information.

IV. Neurobiological Models of Adolescents’ Social Influence Susceptibility

Often described as a car in full throttle with ineffective brakes, the adolescent brain was originally thought to be defective in some way (see Payne, 2012 ). However, based on functional and structural magnetic resonance imaging (MRI) research, we now know that the teenage brain is rapidly changing and adapting to its environment in ways that promote skill acquisition, learning, and social growth (see Telzer, 2016 ). Indeed, the adolescent period is marked by dramatic changes in brain development, second only to that seen in infancy. Such changes in the brain uniquely sensitize adolescents to social stimuli in their environment, and may underlie social influence susceptibility – for better or for worse.

Social influence susceptibility may reflect a (1) heightened orientation to social cues, (2) greater sensitivity to social rewards and punishments, and (3) compromised cognitive control. Indeed, adolescence is characterized by changes in neural circuitry underlying each of these processes (see Figure 1 ). For instance, complex social behaviors, including the ability to think about others’ mental states such as their thoughts and feelings, to reason about others’ mental states to inform one’s own behaviors, and to predict what another person will do next during a social interaction ( Frith & Frith, 2007 ; Blakemore, 2008 ) involve the recruitment of brain regions including the temporoparietal junction (TPJ), posterior superior temporal sulcus (pSTS), and the dorsomedial prefrontal cortex (DMPFC). Moreover, the medial prefrontal cortex (MPFC) is involved in thinking about the self and close others ( Kelley et al., 2002 ; Johnson et al., 2002 ). These brain regions tend to be more activated among adolescents relative to adults when processing social information ( Blakemore, den Ouden, Choudhury, & Frith, 2007 ; Burnett, Bird, Moll, Frith, & Blakemore, 2009 ; Gunther Moor et al., 2012 ; Pfeifer et al., 2009 ; Van den Bos, Van Dijk, Westenberg, Rombouts, & Crone, 2011 ; Wang, Lee, Sigman, & Dapretto, 2006 ; Somerville et al., 2013 ), underscoring adolescence as a key period of social sensitivity ( Blakemore, 2008 ; Blakemore & Mills, 2014 ).

Neural regions involved in social cognition (yellow), cognitive control (blue), and affective processing (red).

Brain regions involved in affective processing include the ventral striatum (VS), which is implicated in reward processing, including the receipt and anticipation of primary and secondary rewards ( Delgado, 2007 ), the orbitofrontal cortex (OFC), which is involved in the valuation of rewards and hedonic experiences ( Saez et al., 2017 ; Kringelbach, 2005 ), and the amygdala, which is involved in detecting salient cues in the environment, responding to punishments, and is activated to both negative and positive emotional stimuli ( Hamann, Ely, Hoffman, & Kilts, 2002 ). Compared to children and adults, adolescents show heightened sensitivity to rewards in the VS ( Galvan et al., 2006 ; Ernst et al., 2006 ; Eshel et al., 2007 ), particularly in the presence of peers ( Chein et al., 2010 ). Adolescents also show heightened VS and amygdala activation to socially appetitive stimuli ( Perino et al., 2016 ; Somerville et al., 2011 ). Thus, adolescents may be uniquely attuned to salient social rewards in their environment.

Finally, brain regions involved in regulatory processes include lateral and medial areas of the prefrontal cortex (e.g., VLPFC, DLPFC, MPFC, ACC). These regions are broadly involved in cognitive control, emotion regulation, goal directed inhibitory control, and serve as a neural brake system ( Wessel et al., 2013 ). Both age-related increases and decreases in PFC activity have been reported across development, such that some studies find that adolescents show heightened PFC activation compared to adults, whereas other studies report adolescent suppression of the PFC ( Bunge et al., 2002 ; Booth et al., 2003 ; Durston et al., 2006 ; Marsh et al., 2006 ; Rubia et al., 2007 ; Velanova et al., 2009 ). Such discrepant developmental patterns of activation have been theorized to underlie flexibility and learning, promoting exploratory behavior in adolescence (see Crone and Dahl, 2012 ).

Based on emerging developmental cognitive neuroscience research, many theoretical models have been proposed to describe adolescents’ neurobiological sensitivity to social context (see Schriber & Guyer, 2016 ). While several of these models explain neural changes that underlie vulnerabilities during adolescence (e.g., heightened risk taking and psychopathology; Casey, Jones, & Hare, 2008 ; Steinberg, 2008 ; Ernst, Pine, & Hardin, 2006 ), these models can be useful heuristics for broadly describing adolescent brain development and social sensitivity, as well as opportunities for positive adjustment (but see Pfeifer & Allen, 2012 , 2016 , for why these models are too simplified).

A. Imbalance Model

The Imbalance Model ( Somerville, Jones, & Casey, 2010 ; Casey et al., 2008 ) proposes that the subcortical network, comprising neural regions associated with the valuation of rewards (e.g., ventral striatum (VS)), matures relatively early, leading to increased reward seeking during adolescence, whereas the cortical network, comprising neural regions involved in higher order cognition and impulse control (e.g., ventral and dorsal lateral prefrontal cortices (VLPFC, DLPFC)), gradually matures over adolescence and into adulthood. The differential rates of maturation in the cognitive control and affective systems creates a neurobiological imbalance during adolescence, which is thought to bias adolescents towards socioemotionally salient and rewarding contexts during a developmental period when they are unable to effectively regulate their behavior (see Figure 2 ).

Imbalance Model of adolescent brain development. Earlier developmental of affective, reward-related activation (red line) and relatively later and more protracted development of cognitive control (blue line) result in a neurobiological imbalance during adolescence (depicted by the grey box).

B. Dual Systems Model

The Dual Systems Model discusses a balance between “hot” and “cool” systems ( Metcalfe & Mischel, 1999 ). The cool system focuses on the cognitive control system, which is emotionally neutral, rational, and strategic, allowing for flexible, goal-directed behaviors, whereas the hot system focuses on the emotional system, which is emotionally reactive and driven by desires (see Casey, 2015 ). During adolescence, the hot system is overactive, and the cool system is not yet fully mature. Similar to the Imbalance Model, the Dual Systems Model describes relatively early and rapid developmental increases in the brain’s socioemotional “hot” system (e.g., VS, amygdala, orbitofrontal cortex) that leads to increased reward- and sensation-seeking in adolescence, coupled with more gradual and later development of the brain’s cognitive control “cool” system (e.g., lateral PFC) that does not reach maturity until the late 20s or even early 30s ( Steinberg, 2008 ; Shulman et al., 2016 ). The temporal gap between these systems is thought to create a developmental window of vulnerability in adolescence during which youth may be highly susceptible to peer influence due to the socioemotional nature of peer contexts ( Steinberg, 2008 ). Although children still have relatively immature cognitive control, they do not yet evidence this heightened orientation towards reward-driven behaviors, and adults have relative maturity of cognitive control and strengthened connectivity across brain networks that facilitate top-down regulation of reward-driven activation. Therefore, the temporal gap between affective and regulatory development is only present in adolescence (see Figure 3 ).

Dual Systems Model of adolescent brain development. (A) Adolescence is characterized by hyperactivation of the “hot” socioemotional system (red circle) coupled with later developing cognitive control (blue circle), and immature connectivity (dotted line) between systems, resulting in an ability to engage in effective regulation. (B) Childhood is characterized by not yet maturing “hot” or “cold” systems, whereas adulthood is characterized by mature “hot” and “cold” systems, coupled with effective connectivity (double arrow) between systems.

C. Triadic Neural Systems Model

The Triadic Neural Systems Model includes the cognitive control system as well as two affective systems, an approach, reward-driven system, which centers on the VS, and an avoidance/emotion system, which centers on the amygdala, a brain region involved in withdrawal from aversive cues and avoidance of punishments ( Ernst, 2014 ). Whereas the VS supports reward processes and approach behavior, the amygdala serves as a “behavioral brake” to avoid potential harm ( Amaral, 2002 ), and the PFC serves to orchestrate the relative contributions of the approach and avoidance systems (see Ernst et al., 2006 ). The balance between reward-driven behaviors and harm-avoidant behaviors is tilted, such that adolescents are more oriented to rewards and less sensitive to potential harms, and the immature regulatory system fails to adaptively balance the two affective systems (see Figure 4 ). Thus, adolescents will be more likely to approach, but not avoid, risky and potentially harmful situations, whereas adults’ more mature regulatory system effectively balances approach and avoidance behaviors, thereby decreasing the likelihood of risk behaviors.

Triadic Systems Model of adolescent neurodevelopment. (A) Adolescents show heightened approach behaviors (ventral striatum), are less sensitivity to harm (amygdala), and have an immature regulatory system (PFC) that does not effectively balance the approach and avoidance systems. (B) Adults have mature regulatory capabilities that effectively balance the approach and avoidance systems.

D. Social Information Processing Network

The Social Information Processing Network model (SIPN; Nelson et al., 2005 ; Nelson, Jarcho, & Guyer, 2016 ) proposes that social stimuli are processed by three nodes in sequential order. The detection node first categorizes a stimulus as social and detects its basic social properties. This node includes regions such as the superior temporal sulcus (STS), intraparietal sulcus, fusiform face area, temporal pole, and occipital cortical regions. After a stimulus has been identified, it is processed by the affective node , which codes for rewards and punishments and determines whether stimuli should be approached or avoided. This node includes regions such as the amygdala, VS, and orbitofrontal cortex. Finally, social stimuli are processed in the cognitive-regulatory node , which performs complex cognitive processing, including theory of mind (i.e., mental state reasoning), cognitive inhibition, and goal-directed behaviors. This node includes regions such as the medial prefrontal cortex (MPFC) and dorsal and ventral prefrontal cortices. These three nodes function as an interactive network, largely in a unidirectional way, from detection to affective to cognitive, but there are also bidirectional pathways. Similar to all of the models discussed above, the affective node is particularly reactive and sensitive during adolescence, whereas the cognitive-regulatory node shows more protracted development into adulthood. Each of the models discussed so far suggest that differential neural development and overreliance on subcortical, reward-related regions drives adolescents to seek out (social) rewards in their environment at a developmental period when self-control is still maturing. While social contexts may tip the balance in terms of affective and cognitive control-related activation, these models do not take into consideration neural regions that specifically code for higher-order social cognition.

E. Neurobiological Susceptibility to Social Context Framework

Perhaps the most promising model for understanding adolescents’ susceptibility to social influence, particularly in regards to positive social influence, stems from the Neurobiological Susceptibility to Social Context Framework ( Schriber & Guyer, 2016 ), which is based on other theoretical frameworks including biological sensitivity to context ( Boyce & Ellis, 2005 ) and differential susceptibility to environmental influences ( Belsky & Pluess, 2009 ). This model proposes that individuals vary in their sensitivity to the social environment as a function of biological factors, particularly neural sensitivity to social contexts. While specific neural biomarkers are not specified, Schriber and Guyer (2016) build on the existing models of brain development discussed above to suggest that adolescents with high neurobiological susceptibility can be pushed in a for-better or for-worse fashion, depending on their social environment ( Figure 5 ). In particular, individuals who are not highly sensitive will not be affected by either positive or aversive social environments, whereas highly sensitive individuals will be both more vulnerable to aversive contexts (e.g., negative peer influence effects), but also more responsive to salubrious contexts (e.g., positive peer influence effects). In other words, those who have supportive peers and family will thrive, whereas those who face family or peer rejection will be most vulnerable.

Neurobiological susceptibility to social influence model. Adolescents with high neurobiological susceptibility (blue dashed line) thrive in positive contexts but are vulnerable in negative contexts.

V. Neural Correlates of Peer and Family Influence

While current neurobiological models or cognitive neuroscience research have yet to clearly connect how social influence processes (e.g., social learning theory, social identity theory) map onto neurobiological development, emerging research has begun to highlight how peer and family contexts influence adolescent neurodevelopment. These studies highlight a set of neural candidates to examine as promising indices of adolescents’ susceptibility to social influence. In particular, neural regions involved in (1) affective processing of social rewards and punishments (e.g.,VS, amygdala), (2) social-cognition and thinking about others’ mental states (e.g.,TPJ, MPFC), and (3) cognitive control that facilitates behavioral inhibition (e.g., VLPFC, anterior cingulate cortex (ACC)) show sensitivity to peer and family contexts (see Figure 1 ). Below we review recent research unpacking the neurobiological correlates of peer and family influence, highlighting studies that focus on positive social influence.

A. Peer Relationships and Neurobiological Development in Adolescence

Prior research has largely focused on the supposed monolithic negative influence of peers (e.g., deviancy training) at both the behavioral (e.g., Dishion et al., 1996 ) and neural level ( Chein, Albert, O’Brien, Uckert, & Steinberg, 2011 ). This research supports the widely held notion that adolescents are more likely to take risks in the presence of their peers, and this is modulated by heightened ventral striatum activation, suggesting that peers increase the salient and rewarding nature of taking risks ( Chein et al., 2011 ). However, it is essential to also examine positive peer influences. If adolescents are highly sensitive to peer influence due to heightened neurobiological sensitivity to social context, then in addition to being pushed to engage in negative behaviors (e.g., risk taking), peers should be able to push teens to engage in more positive behaviors (e.g., prosocial behaviors).

Positive peer influence.

In a recent neuroimaging study, we examined whether peer presence and positive feedback affected adolescents’ prosocial behaviors (donation of tokens to their group in a public goods game) and associated neural processing ( Van Hoorn, Van Dijk, Güroğlu, & Crone, 2016 ). Adolescents donated significantly more to a public goods group when they were being observed by their peers, and even more so when receiving positive feedback (i.e., thumbs up) from their peers. Prosocial decision-making in the presence of peers was associated with enhanced activity in several social brain regions, including the dorsal medial prefrontal cortex (dmPFC), TPJ, precuneus and STS. Effects in the dmPFC were more pronounced in early adolescents (12–13 year olds) than mid-adolescents (15–16 year olds), suggesting that early adolescence may be a window of opportunity for prosocial peer influence. Interestingly, these findings revealed that social brain regions, rather than affective reward-related regions, underlie prosocial peer influence. These findings underscore early adolescents as particularly sensitive to social influence, but in a way that promotes positive, prosocial behavior.

Researchers have also examined how the context of risk-promoting or risk-averse social norms affects adolescents’ risk taking. In a recent study, researchers had adolescents complete a cognitive control task during an fMRI scan, and used a “brain as predictor of behavior” approach to test how the neural correlates of cognitive control affect adolescents’ conformity to peer influence ( Cascio et al., 2015 ). One week following the scan, adolescents returned to the lab to undergo a simulated driving session in the presence of either a high- (e.g., indicating their driving behavior is more risky than the participant) or low- (e.g., indicating their behavior is less risky and more cautious than the participant) risk-promoting peer. Adolescents made fewer risky choices in the presence of low-risk peers compared to high-risk peers. At the neural level, adolescents who recruited regions involved in cognitive control(e.g., lateral PFC ) during the cognitive control task were more influenced by their cautious peers, such that cognitive control-related activation was associated with safer driving in the presence of cautious peers. Such activation was not associated with being influenced by risky peers or driving behavior when alone. Engagement of the PFC during the cognitive control task may represent a neurobiological marker for more thoughtful and deliberative thinking, allowing adolescents to override the tendency to be risky and instead conform to their more cautious peers’ behavior. This study highlights that social influence susceptibility may be a regulated process as opposed to a lack of inhibition, and also points to the positive side of peer conformity.

Supportive peer friendships.

In addition to examining how peers may influence adolescents to engage in more positive behaviors, researchers have examined the role of supportive peer friendships in buffering adolescents from negative outcomes. The need for social connection and peer acceptance is one of the most fundamental and universal human needs ( Baumeister & Leary, 1995 ). As peer relationships increase in importance during adolescence, close friendships become their primary source of social support ( Furman & Buhrmester, 1992 ). When adolescents do not feel socially connected, it poses serious threats to their well-being. Fortunately, social connection and close friendships can buffer adolescents from the distress associated with negative peer relations. In a recent study, we tested the stress-buffering model of social relationships ( Cohen, Gottlieb, & Underwood, 2001 ) to examine whether supportive peer relationships can attenuate the negative implications of chronic peer conflict ( Telzer, Fuligni, Lieberman, Miernicki, & Galvan, 2015 ). Adolescents reporting chronic peer conflict engaged in more risk-taking behavior, and at the neural level, showed increased activation in the ventral striatum when making risky choices. But those adolescents reporting high peer support were completely buffered from these effects – those experiencing high peer conflict did not engage in more risk taking or show heightened ventral striatum activation during risky decisions when they had a close friend. These findings highlight the vital role that supportive friends play. Even in the face of peer conflict, having a close friend can provide the means to feel connected to a social group and receive emotional support and guidance, which may provide them with a means of coping with stress.

B. Family Relationships and Neurobiological Development in Adolescence

In addition to investigating the role of peers on positive adolescent adjustment, developmental social neuroscientists have also examined the influence of the family. In the following section, we review neuroimaging work on how the family context contributes to adolescent adjustment through family norms and values, positive family relationships, and parental monitoring.

Familial norms and values.

One way researchers have examined familial influence on positive youth adjustment and brain development is to examine the internalization of family values. Often referred to as “familism” or “family obligation,” youth from Latin American families, for example, stress the importance of spending time with the family, high family unity, family social support, and interdependence for daily activities ( Cuellar, Arnold, & Maldonado, 1995 ; Fuligni, 2001 ). The internalization of strong family obligation values is associated with lower rates of substance use ( Telzer, Gonzales, & Fuligni, 2014 ) and depression ( Telzer, Tsai, Gonzales, & Fuligni, 2015 ) in Mexican-American adolescents, underscoring family obligation as an important cultural resource. At the neural level, we found that higher family obligation values were associated with greater activation in the DLPFC during a cognitive control task, which was associated with better decision making skills ( Telzer, Fuligni, Lieberman, & Galvan, 2013a ), suggesting that by putting their family’s needs first and delaying personal gratification for their family, youth may develop more effective cognitive control, helping them to avoid the impulse to engage in risky behaviors. In addition, higher family obligation values were associated with lower activation in the VS during a risk-taking task, which was associated with less self-reported risk-taking behavior ( Telzer et al., 2013a ). Youth with stronger family obligation values report more negative consequences for engaging in risk taking, as it may reflect poorly upon their family ( German, Gonzales, & Dumka, 2009 ). Thus, risk taking itself may become less rewarding, as evidenced by dampened VS activation.

We also examined whether the rewarding and meaningful nature of family obligation itself offsets the rewards of risk taking. First, we found that engaging in family obligation (i.e., making decisions that benefit the family) recruits the VS, even more so than gaining a personal reward for the self, suggesting that decisions to make sacrifices for the family are personally meaningful and rewarding ( Telzer, Fuligni, & Galvan, 2016 ). Secondly, we correlated VS activation during the family obligation task with VS activation during the risk-taking task described above. Adolescents who had heightened VS activation during the family obligation task showed less activation in the same brain region during the risk-taking task, suggesting that the rewarding nature of family obligation may make risk taking comparatively less rewarding ( Telzer et al., 2016 ). Importantly, increased activation in the VS during the family obligation task predicted longitudinal declines in risky behaviors and depression, whereas increased VS activation during the risk taking task predicted increases in psychopathology ( Telzer, Fuligni, Lieberman, & Galvan, 2013b , Telzer et al., 2015 ). Thus, finding meaning in social, other-focused behaviors (i.e., family obligation) can promote positive youth adjustment, whereas being oriented towards more self-focused behaviors (i.e., risk taking) is a vulnerability. Together, these findings suggest that the internalization of important family values is rewarding and meaningful, buffering adolescents from both risk taking and depression.

Positive family relationships.

Besides family values, the quality of family relationships also influences adolescents’ positive adjustment – high family support and cohesion and low conflict are associated with a host of positive outcomes, including better school performance, lower substance use, and lower internalizing symptoms ( Melby et al., 2008 ; Samek et al., 2015 ; Telzer & Fuligni, 2013 ). According to social control theories, adolescents who are close to their parents feel obligated to act in non-deviant ways, whereas adolescents in conflictual families do not feel obligated to conform to their parents’ expectations and will be more likely to engage in risky behaviors ( Bahr et al., 2005 ). Thus, strong family relationship quality can buffer adolescents from risk taking, perhaps by making risk taking less rewarding. In one longitudinal fMRI study, we examined changes in the quality of family relationships, paying particular attention to three dimensions of positive family interactions: high parental support (e.g., their parents respected their feelings), adolescents’ spontaneous disclosure (e.g., telling their parents about their friends), and low family conflict (e.g., having a fight or argument with their parents). Adolescents who reported improvements in the quality of their family interactions showed longitudinal declines in risk taking, which was mediated by declines in VS activation during a risk-taking task (Qu, Fuligni, Galvan, Lieberman, & Telzer, 2015). This study suggests that increases in positive family relationships may provide adolescents with a supportive environment, increasing their desire to follow their parents’ expectations, which may dampen their subjective sensitivity to rewards during risk taking. In addition to examining cohesion and conflict, this study assessed adolescents’ disclosure to their parents. Given that adolescents spend increasingly less time with their parents than do children ( Lam, McHale, & Crouter, 2012 ; 2014 ), voluntary disclosure of their activities may provide opportunities for parents to give their children advice and supervision, helping them develop the skills to avoid risks and devalue the rewarding nature of risk taking.

Parental monitoring.

In addition to adolescents’ spontaneous disclosure, parental monitoring plays a key influence on adolescents’ decisions to avoid deviant behaviors. Yet, during the adolescent years, parents tend to decrease their supervision of their children, and adolescents are more likely to make maladaptive decisions during unsupervised time or in the presence of their peers ( Richardson, Radziszewska, Dent, & Flay, 1993 ; Beck, Shattuck, & Raleigh, 2001 ; Borawski, Ievers-Landis, Lovegreen, & Trapl, 2003 ). In a recent study, we tested how the presence of parents changes the way adolescents make decisions in a risky context. During an fMRI scan, adolescents played a risky driving game twice: once alone, and once with their mother present and watching. Whereas adolescents take greater risks when their friends are watching them during this same task ( Chein et al., 2011 ), we found that adolescents made significantly fewer risks when their mother was present ( Telzer, Ichien, & Qu, 2015 ).

At the neural level, the presence of friends is associated with more VS activation (Chein et al. 2010), whereas the presence of mothers is associated with less VS activation when making risky choices ( Telzer, Ichien, & Qu, 2015 ). Importantly, this protective role is specific to mothers, as we did not find the same decrease in risk taking or ventral striatum activation when an unknown adult was present (Guassi Moreira & Telzer, in press). Together, these findings suggest that peers may increase the rewarding nature of risk taking, whereas mothers may take the fun away. In addition, neural regions involved in cognitive control (e.g., VLPFC, MPFC), were more activated when their mother was present than when alone or in the presence of an unknown adult, suggesting that maternal presence may facilitate more mature and effective neural regulation via top-down inhibitory control from prefrontal regions. Finally, after making a risky decision, adolescents recruited regions involved in mentalizing (e.g., TPJ) more when their mother was present than an unknown adult, suggesting that adolescents are more sensitive to their mother’s perspective following a brief instance of misbehavior (i.e., running the yellow light). Together, these findings suggest that the presence of mothers alters the way adolescents make risky decisions and may provide an important scaffolding role, helping adolescents avoid risks by decreasing the rewarding nature of risks and promoting more effective cognitive control.

C. Simultaneous Role of Family and Peer Relationships on Adolescent Brain Development

Although few neuroimaging studies have examined the simultaneous influence of family and peers on adolescent development, there is emerging evidence suggesting that adolescents’ choices are affected, in part, by differential neural sensitivity to family versus peers. In order to capture how behavior and brain function change in the context of family and peers, researchers have mainly examined within-person differences between decisions that affect a family member (primarily parents) compared to decisions that affect peers. In addition, novel research designs have recently stimulated investigations of the simultaneous influence of both parent and peer influence on adolescent decision making, which are also discussed in this section.

Emotional reactivity to peers and parents.

Prior research consistently characterizes adolescence as a time of social reorientation from parent to peer influences, a process thought to be supported by developmental changes within several affective and social cognitive brain regions ( Nelson et al., 2005 ). However, only recently has research emerged showing that this social reorientation at the behavioral level is paralleled by functional changes at the neural level, such that simply processing peer versus parent faces elicits different neural responses in regions involved in socioemotional processing during adolescence. In a study examining adolescents’ emotion perception of their mother’s, father’s and an unknown peer’s faces, adolescents exhibited greater activation in regions implicated in social (PCC, pSTS, TPJ) and affective (VS, amygdala, hippocampus) processing when viewing their peer relative to parent faces (no difference between processing maternal or paternal stimuli; Saxbe, Del Piero, Immordino-Yang, Kaplan, & Margolin, 2015 ). This illustrates that the neural correlates underlying socioemotional processing change over the course of adolescence as the salience of peers increases relative to family. Moreover, although adolescents, on average, showed greater activation in the PCC and precuneus to peer versus parent faces, those who showed less of this effect (i.e., did not show greater activation in these regions to peer over parent faces) engaged in lower levels of risk-taking behaviors and affiliation with deviant peers. Thus, less recruitment of regions involved in social cognition (e.g., mentalizing) toward peers relative to parents may help to diminish the social value of peer influence on negative behaviors during adolescence.

Vicarious rewards for peers and parents.

Differential neural sensitivity to peers versus parents can be leveraged to promote adaptive decision making during adolescence, specifically by encouraging vicarious learning about other-oriented behaviors. Even in the absence of a personally experienced reward, the act of seeing or imagining others experience rewards (i.e., vicarious rewards) elicits activation in reward-related regions (VS) and promotes prosocial motivations ( Mobbs et al., 2009 ). Given the heightened salience of peer and parent influence during adolescence, it is important to explore whether exposure to vicarious rewards that affect close others might reinforce positive choices. Vicarious learning, especially through observing the positive behaviors and outcomes of close others, can facilitate the internalization of positive social norms and increase motivation to model similar behaviors in the future, which is consistent with social learning theory. A recent study examined VS activation during a risk-taking task, where the potential gains and losses could affect adolescents’ mothers or best friends ( Braams & Crone, 2016 ). Striatal activation peaked in adolescence compared to childhood and young adulthood when youth took risks to win money for their mothers, but not for their peers. Self-report data further demonstrated a positive association between relationship quality and the extent to which adolescents enjoyed taking risks to win money for both their mothers and best friends. Therefore, developmental changes in reward sensitivity and relationship quality can affect adolescents’ motivation to engage in risky behaviors that affect others over time. Indeed, a new perspective from developmental neuroscience proposes that, in some contexts, adolescents may be taking risks with the explicit intention of helping others ( Do et al., 2017 ), a process that may be supported by neural reactivity in reward-related regions to the experience of vicarious rewards for close others.

Balancing conflicting social influence from peers and parents.

A common feature of adolescent decision making is the balance of conflicting social information from parents and peers. This is an important area of inquiry, as peer and family values and norms often differ, resulting in norm conflicts that inevitably affect adolescent decision making and beg for reconciliation. In one of the first developmental studies to examine the neural correlates of both parental and peer influence on attitude change, we first asked adolescents, their primary caregiver, and several peers from their schools to each independently evaluate artwork stimuli prior to their scan ( Welborn et al., 2015 ). Artwork was selected, as it tends to be neutral stimuli where attitudes may be swayed by influence. Adolescents completed an fMRI session a few weeks later, where they were shown their parents’ or peers’ real evaluations of the same pieces of artwork before re-evaluating the stimuli. Adolescents were more likely to change their own attitudes to bring them in line with those of their parents compared to their peers. At the neural level, adolescents exhibited greater activation in regions involved in mentalizing (TPJ, precuneus), reward processing (ventral medial prefrontal cortex, VMPFC), and self-control (VLPFC) when they were influenced by both their peers and parent, with no difference between the source of social influence. Moreover, greater activation in these task-responsive regions predicted a greater likelihood for youth to shift their attitudes in favor of the corresponding source of influence. Thus, although family and peers influence adolescents through similar neural mechanisms (involved in mentalizing, reward processing, and regulation), individual differences in this neurobiological sensitivity might differentially predict adolescents’ tendency to adopt the attitudes and/or behaviors of their family or peers.

While prior research has examined neural differences between social influence from family and peers, no study to date has delineated how youth incorporate the simultaneous influence of their family and peers into their decisions and behaviors. When there is a discrepancy between peers’ and parents’ attitudes about a behavior, adolescents often need to simultaneously weigh the relative value of these conflicting attitudes when deciding whether to personally endorse that behavior, which may differ depending on if it is positive or negative. Over time, their decision to conform to the attitudes of one influence over the other can have important implications for reinforcing their participation in those behaviors. For example, an adolescent who endorses drug use as a means of conforming to the attitudes favored by their peers, but is discouraged by their parents, may be more likely to do drugs over time. We recently examined this process in an fMRI study, where we showed adolescents their parents’ and peers’ evaluations of positive and negative behaviors at the same time, each of which differed from each other and were manipulated to conflict with adolescents’ initial evaluations (Do, McCormick, & Telzer, unpublished data). To measure the extent to which adolescents were affected by conflicting social information, adolescents indicated whether they agreed with their parent or peers’ evaluations of each behavior. On average, adolescents showed differences in neural activation within affective and reward-related regions when agreeing more with their peers than parents (collapsed across both positive and negative behaviors), highlighting the important role of these regions in reconciling conflicting social information from parents and peers, and ultimately agreeing with the peer. Overall, this research highlights the need to further investigate how interactions between family and peer influence differentially affect adolescent decision making, with the goal of identifying opportunities to leverage adolescents’ increased social and neurobiological susceptibility in favor of positive developmental outcomes.

VI. Conclusions and future directions

Social influences from peers and family have a profound impact on positive youth adjustment. Although susceptibility to social influence is often viewed as a vulnerability in adolescent development, particularly in the peer domain (and arguably so, given the evidence for peer-related increases in risk taking behaviors), we reviewed empirical support that underscores the positive side of susceptibility to social influence. Peers and families provide an opportunity for social adjustment, with the potential to redirect negative trajectories and increase positive outcomes. With empirical evidence showing that social influence relates to positive adjustment, it is key to capitalize on the social context and use this time as a period of investment, perhaps especially during middle school when adolescents are thought to be most socially sensitive ( Knoll, Magis-Weinberg, Speekenbrink, & Blakemore, 2015 ; Van Hoorn et al., 2016b). Indeed, recent prevention programs designed to decrease problem behaviors (e.g., tobacco use, peer victimization) and/or increase positive behaviors (e.g., prosocial behaviors), have successfully applied aspects of social learning and social identity theories in the promotion of positive classroom norms and use of socially salient referent peers to change negative attitudes ( Van Luijk et al., 2011 ; Paluck & Shepherd, 2012 ). Despite increasing attention to the positive side of social influences and its application in interventions, further research is needed to fully capture the inherent complexities of the social influence process and its relation to positive youth adjustment. With increased understanding of the social influence processes involved in deviancy training, we could modify and apply them to prosocial training, in which youth are exposed to more positive social influences.

Emerging evidence from developmental neuroscience has identified neurobiological processes through which peers and family influence decision-making and positive adjustment via changes in functional brain activity. Indeed, social influences from peers and parents are neurally represented in the adolescent brain by activity in a collection of cognitive, affective and social brain areas. Adolescents’ decisions and positive adjustment outcomes are likely affected by differential neural sensitivity to family and peers, and future studies should further probe the neural mechanisms of simultaneous and interactive influence from these two salient social sources. Given that social influence often occurs on a more implicit and unconscious level, the developmental social neuroscience perspective provides an informative additional layer of assessment that complements behavioral self-report and experimental methods.

While the peer and family contexts are especially critical in understanding positive adolescent development ( Van Ryzin et al., 2012 ), this is admittedly a narrow view of the social context. Other salient persons in the immediate environment may also be potent sources of social influence, such as sports team coaches, teachers, and mentors. Large individual differences exist in such proximal social contexts, and it is important to consider these individual differences within the larger social network (i.e., school context, neighborhoods, and larger community; Bronfenbrenner & Morris, 2006 ). Some youth may have access to mentoring opportunities in their local neighborhood (both setting an example as mentor and learning as mentee), whereas others do not, which may greatly impact the form and power of social influence. While those with no access to mentoring opportunities are perhaps more exposed to social influences from parents and siblings at home, youth with a larger social network who play sports or music with peers may be more exposed to peer norms. Hence, in order to help youth thrive, it is important for future work to study the complex influences from the social context on positive youth development. And perhaps, the question posed at the start of the chapter will eventually be complemented with “If your friends would [insert something positive here], then would you too?” .

Acknowledgments

This work was supported by the National Institutes of Health (R01DA039923 to Telzer) and the National Science Foundation (SES 1459719 to Telzer).

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Research Article

Social Influence and the Collective Dynamics of Opinion Formation

* E-mail: [email protected]

Affiliation Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, Germany

• Mehdi Moussaïd, 
• Juliane E. Kämmer, 
• Pantelis P. Analytis, 
• Hansjörg Neth

• Published: November 5, 2013
• https://doi.org/10.1371/journal.pone.0078433
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Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: ( i ) the expert effect , induced by the presence of a highly confident individual in the group, and ( ii ) the majority effect , caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

Citation: Moussaïd M, Kämmer JE, Analytis PP, Neth H (2013) Social Influence and the Collective Dynamics of Opinion Formation. PLoS ONE 8(11): e78433. https://doi.org/10.1371/journal.pone.0078433

Editor: Attila Szolnoki, Hungarian Academy of Sciences, Hungary

Received: May 31, 2013; Accepted: September 10, 2013; Published: November 5, 2013

Copyright: © 2013 Moussaïd et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This research has been supported by the Max Planck Society. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

In many social and biological systems, individuals rely on the observation of others to adapt their behaviors, revise their judgments, or make decisions [1] – [4] . In human populations, the access to social information has been greatly facilitated by the ongoing growth of communication technology. In fact, people are constantly exposed to a steady flow of opinions, advice and judgments of others about political ideas, new technologies, or commercial products [5] . When facing the opinions of peers on a given issue, people tend to filter and integrate the social information they receive and adjust their own beliefs accordingly [6] , [7] . At the scale of a group, repeated local influences among group members may give rise to complex patterns of opinion dynamics such as consensus formation, polarization, or fragmentation [8] – [11] . For example, it has been shown that people sharing similar extreme opinions, such as racial prejudices, tend to strengthen their judgment and confidence after interacting with one another [12] . Similar mechanisms of opinion dynamics can take place in a variety of social contexts, such as within a group of friends exchanging opinions about their willingness to get vaccinated against influenza [13] , [14] . At even larger scales, local influences among friends, family members, or coworkers — often combined with the global effects of mass media — constitute a major mechanism driving opinion formation during elections, shaping cultural markets [15] , producing amplification or attenuation of risk perceptions [16] , [17] , and shaping public opinion about social issues, such as atomic energy or climate change [18] .

Given the remarkably large scope of social phenomena that are shaped by social influence and opinion dynamics, it is surprising that the behavioral mechanisms underlying these processes remain poorly understood. Important issues remain open: How do people adjust their judgment during social interactions? What are the underlying heuristics of opinion adaptation? And how do these local influences eventually generate global patterns of opinion change? Much of the existing modeling work about opinion dynamics has been addressed from a physics-based point of view, where the basic mechanisms of social influence are derived from analogies with physical systems, in particular with spin systems [19] – [23] . The wide variety of existing models assumes that individuals hold binary or continuous opinion values (usually lying between -1 and 1), which are updated over repeated interactions among neighboring agents. Different models assume different rules of opinion adaptation, such as imitation [24] , averaging over people with similar opinions [25] , [26] , following the majority [27] , or more sophisticated equations [8] , [22] . Although informative as to the complex dynamics that can possibly emerge in a collective context, these simulation-based contributions share a common drawback: the absence of empirical verification of the models’ assumptions [28] . Indeed, it is difficult to track and measure how opinions change under experimental conditions, as these changes depend on many social and psychological factors such as the personality of the individuals, their confidence level, their credibility, their social status, or their persuasive power [18] . In other disciplines such as psychology and cognitive science, laboratory experiments have been conducted to study how people integrate feedback from other individuals to revise their initial answers to factual questions [6] , [29] , [30] . However, the findings of local rules of opinion adaptation have not yet been used to study the collective dynamics of the system, and it remains unclear how social influence plays out in larger scale social contexts over time [31] .

The present work draws upon experimental methods inspired by social psychology and theoretical concepts of complex systems typical of statistical physics. First, we conducted controlled experiments to describe the micro-level mechanisms of social influence, that is, how individuals revise their initial beliefs after being exposed to the opinion of another person. Then, we elaborated an individual-based model of social influence, which served to investigate the collective dynamics of the system. In a first experiment (see Materials & Methods), 52 participants were instructed to answer a series of 32 general knowledge questions and evaluate their confidence level on a scale ranging from 1 ( very unsure ) to 6 ( very sure ). This baseline experiment was used to characterize the initial configuration of the system before any social influence occurs. In a second experimental session, 59 participants answered 15 questions in the same way but were then exposed to the estimate and confidence level of another participant (henceforth referred to as “feedback”) and asked to revise their initial answer. This procedure renders opinion changes traceable, and the effects of social influence measureable at the individual level. Moreover, changes in confidence were tracked as well, by asking participants to evaluate their confidence level before and after social influence. Despite empirical evidence suggesting that changes of opinion and confidence are intimately related [29] , and theoretical work emphasizing the important role of inflexible, highly confident agents [32] , [33] , this aspect of social influence remains poorly understood. Following the methods of existing experiments, we deliberately asked neutral, general knowledge questions, which allows capturing the mechanisms of opinion adaptation while controlling its emotional impact [6] , [30] . By exploring a simple model derived from our observations, we demonstrate that the collective dynamics of opinion formation in large groups of people are driven by two major “attractors of opinion”: ( i ) the presence of a highly confident individual and ( ii ) the presence of clusters of low-confidence individuals sharing a similar opinion. In particular, we show that a critical amount of approximately 15% of experts is necessary to counteract the attractive effect of a large majority of lay individuals. As people are embedded in strongly connected social networks and permanently influence one another, these results constitute a first step toward a better understanding of the mechanisms of propagation, reinforcement, or polarization of ideas and attitudes in modern societies.

Experimental results

We first use the data from the first experiment to characterize the initial configuration of the system before any social influence occurs, that is, how opinions are initially distributed and how the accuracy and confidence of the answers are correlated with each other.

As shown in the example in Fig. 1A , the initial distribution of opinions has a lognormal shape, with a typical long tail indicating the significant presence of outliers. For each of 32 items we performed a Kolmogorov-Smirnov normality test of log( O i ), where O i is the initial opinion of individual i . The test yielded p-values above.05 for 84% of the items, indicating that the null hypothesis cannot be rejected at the 5% significance level for these items. The remaining 16% still had reasonably high p-values (always >10 −3 ), suggesting that the initial opinions O i indeed follow a lognormal distribution.

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https://doi.org/10.1371/journal.pone.0078433.g001

https://doi.org/10.1371/journal.pone.0078433.g002

To explore the wisdom of crowds, we compared the accuracy of various aggregating methods before and after social influence occurred ( Fig. 2A ). Our results agree with previous findings [29] , [35] . We find that the error distributions tend to become widespread, now covering a greater proportion of also high error values after social influence, regardless of the aggregating method.

https://doi.org/10.1371/journal.pone.0078433.g003

1. Keep initial opinion , when individuals do not change their judgment after receiving a feedback, that is: R i  =  O i , where R i is the revised opinion of participant i .

2. Make a compromise , when the revised opinion falls in between the initial opinion O i and the feedback O j : min( O i , O j )< R i <max( O i , O j ).

3. Adopt other opinion , when an individual i adopts the partner’s opinion: R i  =  O j .

https://doi.org/10.1371/journal.pone.0078433.g004

Here, all the parameter values were directly extracted from the observations ( Fig.3B and Fig.4 ).

Collective dynamics

Having characterized the effects of social influence at the individual level, we now scale up to the collective level and study how repeated influences among many people play out at the population scale. Because the macroscopic features of the system are only visible when a large number of people interact many times, it would be extremely difficult to investigate this under laboratory conditions. Therefore, we conducted a series of numerical simulations of the above model to investigate the collective dynamics of the system.

The initial conditions of our simulations correspond to the exact starting configurations observed in our experiments (i.e., the precise opinion and confidence values of all 52 participants observed in the first experiment) [36] . In each simulation round, the 52 individuals are randomly grouped into pairs, and both individuals in a pair update their opinions according to the opinion of the other person, as predicted by our model. Thus, each individual is both a source and the target of social influence. We performed N  = 300 rounds of simulated interactions, where N has been chosen large enough to ensure that the system has reached a stationary state. Here, we make the assumption that the decision tree that has been extracted from our experiment remains the same over repeated interactions. This assumption is reasonable to the extent that the outcome of the decision tree (i.e. the strategy that is chosen) depends on the confidence level of the individual, which is expected to change as people receive new feedback. In such a way, the strategies that will be selected by individuals are connected to the individual history of past interactions.

Fig. 5 shows the dynamics observed for three representative examples of simulations. Although a certain level of opinion fragmentation still remains, a majority of individuals converge toward a similar opinion. As shown by the arrow maps in Fig.5 , the first rounds of the simulation exhibit important movements of opinions among low-confidence individuals (as indicated by the large horizontal arrows for confidence lower than 3), without increase of confidence (as shown in Fig. S2 ). After a certain number of rounds, however, a tipping point occurs at which a critical proportion of people meet up in the same region of the opinion space. This creates a subsequent increase of confidence in this zone, which in turn becomes even more attractive to others. This results in a positive reinforcement loop, leading to a stationary state in which the majority of people end up sharing a similar opinion. This amplification process is also marked by a sharp transition of the system’s global confidence level ( Fig. S2 ), which is a typical signature of phase transitions in complex systems [2] .

For each example, the initial opinion map is shown on the left-hand side (experimental data), and the final opinion map after N  = 300 rounds of simulations on the right-hand side. The opinion maps represent the proportion of individuals with a given opinion ( x -axis) and a given confidence level ( y -axis). As in Fig. 1, the normalized opinion is the actual opinion divided by the true value. The correct answer is represented by the red dashed lines (corresponding to a value of 1). Outliers with normalized opinion greater than 2 are not shown. The arrow maps represent the average movements over both opinion and confidence dimensions during simulations. Examples 1, 2, and 3 correspond to the questions “ What is the length of the river Oder in kilometers? ”, “ How many inhabitants has the East Frisian island Wangerooge? ”, and “ How many gold medals were awarded during the Olympics in China in 2008? ”, respectively. The final convergence point may be determined by a dense cluster of low confidence individuals, as illustrated by Example 2 ( majority effect ), or by a few very confident individuals as in Example 3 ( expert effect ).

https://doi.org/10.1371/journal.pone.0078433.g005

An intriguing finding of our simulations is that the collective opinion does not converge toward the average value of initial opinions (a correlation test yields a nonsignificant effect with a coefficient c  = -.05). The correlation between the convergence point and the median value of the initial opinions is significant ( p  = .03) but the relatively moderate correlation coefficient c  = 0.46 suggests that this relation remains weak. Likewise, the system does not systematically converge toward or away from the true value (nonsignificant effect with a coefficient c  = .11). Instead, the simulations exhibit complex collective dynamics in which the combined effect of various elements can drive the group in one direction or another. In agreement with previous works [15] , the collective outcome appears to be poorly predictable and strongly dependent on the initial conditions [36] . Nevertheless, we identified two major attractors of opinions that exert an important social influence over the group:

• The first attractor is the presence of a critical mass of uncertain individuals who happen to share a similar opinion. In fact, when such a cluster of individuals is initially present in the system­—either by chance or because individuals share a common bias—the rest of the crowd tends to converge toward it, as illustrated by Fig. 5 -Example2. This majority effect is typical of conformity experiments that have been conducted in the past [37] , where a large number of people sharing the same opinion have a strong social influence on others.
• The second attractor is the presence of one or a few highly confident individuals, as illustrated by Fig. 5 -Example3. The origin of this expert effect is twofold: First, very confident individuals exert strong persuasive power, as shown by the influence map. Second, unconfident people tend to increase their own confidence after interacting with a very confident person, creating a basin of attraction around that person’s opinion [38] , [39] .

Our simulations show that the majority effect and the expert effect are not systematically beneficial to the group, as both attractors could possibly drive the group away from the truth ( Fig. 5 -Example 2). What happens in the case of conflicting interests, when the expert and the majority effects apply simultaneously and disagree with each other ( Fig. 5 -Example 3)? To investigate this issue, we conducted another series of simulations in which a cluster of low-confidence individuals sharing the same opinion O maj , is facing a minority of high-confidence experts holding another opinion O exp . As shown by Fig. 6A , the majority effect overcomes the expert effect when the proportion of experts p Exp is lower than a certain threshold value located around 10%. However, as p Exp increases from 10%, to 20% a transition occurs and the convergence point shifts from the majority to the experts’ opinion. Remarkably, this transition point remains stable even when a proportion p Neut of neutral individuals (defined as people with random opinions and a low confidence level) are present in the system ( Fig. 6B ). As p Neut increases above 70%, however, noise gradually starts to dominate, leading the expert and the majority effects to vanish. The tipping point occurring at a proportion of around 15% of experts appears to be a robust prediction, not only because it resists to a large amount of system noise ( Fig. 6B ), but also because a previous theoretical study using a completely different approach also reached a similar conclusion [40] .

(A) The evolution of collective opinion when varying the relative proportion of experts p Exp , holding an opinion O exp and a high confidence level C exp  = 6, and the proportion of people in the majority group p maj holding an opinion O maj and a low confidence level randomly chosen in the interval C maj  = [1 3]. Here, the number of neutral individuals is fixed to p Neut  = 0. (B) Phase diagram showing the parameter space where the majority or the expert effects applies, when increasing the proportion of neutral individuals p Neut holding a random opinion and a low confidence level randomly chosen in the interval C uni  = [1 3]. The schematic regions delimited by black or white dashed lines show the zones where the collective opinion converges toward the majority or the expert opinion, respectively. In the transition zone, the collective opinion converges somewhere between O exp and O maj . In some rare cases, the crowd splits into two groups or more.

https://doi.org/10.1371/journal.pone.0078433.g006

In this work, we have provided experimental measurements and quantitative descriptions of the effects of social influence—a key element in the formation of public opinions. Our approach consisted of three steps: using controlled experiments to measure the effects of social influence at the scale of the individual, deriving a simple process model of opinion adaptation, and scaling up from individual behavior to collective dynamics by means of computer simulations.

Scaling up from individual to collective behavior was achieved by means of computer simulations in line with existing approaches in the field of self-organization and complex systems [2] , [9] , [19] . Our simulations allowed us to unravel the precise mechanisms of opinion dynamics in large groups of people, which would have been practically impossible to characterize under laboratory conditions. In particular, an important ingredient underlying the collective dynamics but lacking in previous modeling approaches is the specific interplay between opinion changes and confidence changes. First, confidence serves as a sort of system memory. In fact, over simulation rounds, individuals are less easily influenced by others because their confidence level gradually increases as they receive new feedback. Therefore, simulated individuals do not constantly change their opinion but progressively converge toward a stable value in a realistic manner. Second, the increase of confidence supports the emergence of basins of attraction during collective opinion dynamics by boosting the attractive power of individuals sharing a similar opinion [29] . This process often turns out to be detrimental to the group, because the local amount of confidence may grow artificially in a given region of the opinion space, which provides false cues to others and triggers a snowball effect that may drive the group in an erroneous direction. Interestingly, judgments of high confidence are good indicators of accuracy before social influence occurs, but no longer after people have been exposed to the opinion of others. It is remarkable that even a mild influence has a significant impact on the reliability of high confidence cues, as shown in Fig. 2B . The main problem induced by social influence is that people tend to become more confident after noticing that other people have similar opinions. Therefore, high confidence is an indicator of accuracy when judgments are independent but becomes an indicator of consensus when social influence takes place [43] , [44] .

Our simulation results also identified two elements that can cause such amplification loops: the expert effect—induced by the presence of a highly confident individual, and the majority effect—induced by a critical mass of low-confidence individuals sharing similar opinions. Moreover, the presence of a significant number of neutral individuals holding a random opinion and a low confidence level around these two attractive forces tends to increase the unpredictability of the final outcome [15] . Therefore, neutral individuals make the crowd less vulnerable to the influence of opinion attractors, and thus less predictable. By contrast, recent studies on animal groups have shown that the presence of uninformed individuals in fish schools acts in favor of the numerical majority, at the expense of very opinionated individuals [1] .

Our simulations constitute a valuable tool that allows ( i ) unravelling the underlying mechanisms of the system, ( ii ) forecasting future trends of opinion change, and ( iii ) driving further experimental research and data collection. Nevertheless, it is important to note that the outcome of our simulations requires empirical validation in the future. This could be addressed, for instance, by means of empirical observations over the Web, where one would measure people’s opinion about a social issue over blogs and discussion forums and evaluate how the collective opinion changes over time [45] , [46] . Alternatively, an online experimental approach such as the one elaborated by Salganik et al. seems well suited to the study of opinion dynamics under controlled conditions [15] .

By quantifying the balance of power between the expert effect, the majority effect, and neutral individuals, our research can inform applications regarding the management of situations in which a small opinionated minority challenges a large population of uninformed individuals. For example, the model could help doctors convince a population of laypeople to adopt certain disease prevention methods or reversely prevent extremist groups from taking control of a large group of people.

Materials and Methods

Ethics statement.

The present study has been approved by the Ethics Committee of the Max Planck Institute for Human Development. All participants gave written and informed consent to the experimental procedure.

Experimental design

The experimental part of the study consisted of two distinct experiments: one without social influence (Experiment 1) and one with (Experiment 2). In both experiments, participants entered the laboratory individually and were instructed to answer a series of factual questions displayed on a computer screen. All participants were naïve to the purpose of our experiments and received a flat fee of €8. In Experiment 1, a total of 52 participants ( M age  = 27 years, SD = 9, 50% females) responded to 32 general knowledge questions, which covered the areas sports, nature, geography and society/economy (8 per area; for a complete list of items see Table S1 ). The correct answers to the questions ranged from 100 to 999, which, however, was not known to the participants. Participants were instructed to respond as accurately as possible and to indicate their confidence on a 6-point Likert scale (1 very unsure to 6 very sure ) after having given their spontaneous estimate. Questions were displayed one after the other on the computer screen, and a new question was given only after participants answered the current one. Participants were only informed about the correct answers to the questions after the end of the experiment and therefore could not figure out that the true values always lied in the interval [100 999]. The order of the questions was randomized for each participant. A correlation test of the accuracy of answers and the order of the questions yielded non-significant p-values for 90% of participants with a probability p>0.05, confirming the absence of any learning process over experimental rounds. After the end of the experiments, participants were paid, thanked and released. In Experiment 1, participants were not exposed to the social influence of others. The 1664 data points (corresponding to 52 participants × 32 questions) were used to characterize the features of the initial environment, such as the distribution of answers and the analyses of the confidence levels shown in Fig. 1 , and as a pool of social influence for the second experiment. The same dataset was used to define the initial condition of the simulations presented in Fig. 5 .

In Experiment 2, 59 participants ( M age  = 33 years, SD = 11, 56% females) responded to 15 of the 32 general knowledge questions used in Experiment 1 and indicated their confidence level. Experiment 2 was conducted under the same conditions as in Experiment 1 except that participants were informed that they would receive a feedback from another participant. After each question, the estimate and confidence level of another randomly selected participant from Experiment 1 were displayed on the computer screen, and participants were then asked for a revised estimate and corresponding confidence level. This second dataset made of 59×15 = 885 binary interactions was used to study the effects of social influence, from which we derived the results shown in Figs. 2 , 3 and 4 . The full list of questions is available in Table S1 .

Supporting Information

The distribution of answers for all 32 questions used in the first experiment (Experiment1, see Materials & Methods). The numbers on the upper right corner correspond to the question id , as indicated in the list of questions provided in the table S1. Question id  = 27 has been used for illustrative purpose in the main text ( Fig. 1A ). The normalized answer is the estimate of the participants divided by the true value. The black dashed lines indicate the correct answer (normalized value  =  1). The red and green dashed lines indicate the mean and the median values of the distribution, respectively. The mean values lying farther than 3 are not indicated.

https://doi.org/10.1371/journal.pone.0078433.s001

Three representative examples showing the evolution of participants’ confidence over simulation rounds. Examples 1, 2 and 3 correspond to those shown in Fig. 4 in the main text. The average global confidence is computed by taking the mean value of confidence for all 52 participants. After a few rounds of simulation, a sharp transition occurs toward high confidence levels, attesting for the opinion amplification process.

https://doi.org/10.1371/journal.pone.0078433.s002

Full list of questions used in the study.

https://doi.org/10.1371/journal.pone.0078433.s003

Acknowledgments

We are grateful to Gudrun Rauwolf and Tor Nielsen for their inspiring feedbacks and participation in the work, and Isaac and Jeanne Gouëllo for fruitful discussions. We thank Jack Soll for sharing with us the experimental data from ref. [30] , and two anonymous reviewers for their constructive comments. The authors thank Anita Todd for language editing.

Author Contributions

Conceived and designed the experiments: MM JEK PPA HN. Performed the experiments: MM JEK PPA HN. Analyzed the data: MM JEK PPA. Wrote the paper: MM JEK PPA HN.

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21 Social Influence and Health

Leslie R. Martin is professor and chair of the Department of Psychology at La Sierra; she is also a research psychologist at the University of California, Riverside.

M. Robin DiMatteo is Distinguished Professor of Psychology and UCR Distinguished Teaching Professor at the University of California, Riverside.

• Published: 09 June 2015
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Early in the lives of children, parental influences are strong, and interventions targeting parents are essential to behavior change. In adolescence, peers emerge as critical additions to the influence of family members; their influence can support the growth and maintenance of positive health behaviors, or it can encourage unhealthy choices. Social groups continue to feature prominently in various ways throughout adulthood. A crucial role is played by supportive social networks in the improvement and maintenance of a wide variety of health behaviors, and the availability of normative information affects health choices. Health care providers hold a good deal of power in the practitioner–patient relationship and influence their patients toward health outcomes in a variety of ways. Finally, system-level influences such as public health programs, health-related media messages, and educational interventions can help motivate individuals toward ideal health behaviors.

We are social beings, influenced from our earliest days by those around us. Social influence is particularly important in the realms of health and health behavior. To date, a large corpus of research has shown that the health behaviors we carry out (or fail to accomplish) are shaped by our families, friends, communities, and the media; we look to these sources for information, inspiration, confirmation, reassurance, and motivation.

In 1959 John French and Bertram Raven described social influence as the change effected in an individual’s beliefs, attitudes, or behaviors as a result of the action of someone else. This followed closely on Leon Festinger’s (1954) description of his theory of the processes of social comparison (see also Suls & Wheeler , this volume). Much research has been done over the ensuing decades both on social influence itself and on the specific role that social comparisons play in shaping a wide variety of behaviors, including those that are relevant to health. In particular, the differential outcomes associated with upward versus downward comparisons have been of interest.

Upward comparisons are those in which the self is compared with someone who is in a more favorable position; in the realm of health, this might be a person who is more effectively managing her blood glucose, or who is able to run a mile in a shorter period of time. Downward comparisons, on the other hand, evaluate the self relative to someone who holds a less favorable position. In health terms, this might be someone who is more overweight or who has had less success in managing his blood pressure.

Of the two, upward comparisons are more effective for motivating changes ( Bandura, 1997 ; Corcoran, Crusius, & Mussweiler, 2011 ; Taylor & Lobel, 1989 ). We strive to be like people we admire, and having the model of someone who is successfully engaging in positive health behaviors can encourage and foster our own success. Trying to improve one’s health can sometimes be discouraging, however—it is easy to drift into negative moods and perhaps to feel like giving up after repeatedly succumbing to the temptation to have another dish of ice cream or to remain on the couch after supper rather than going for that walk. In this type of situation, downward comparisons can be useful because they are linked to more positive emotions ( Buunk, Collins, Taylor, Van Yperen, & Dakof, 1990 ; Helgeson & Taylor, 1993 ; Wills, 1981 ). Comparing oneself to someone else who has poorer health or who is even less successful at making changes emphasizes the strides that one has already made, or the advantages that one has; these positive emotional states are incompatible with an “I can’t do it, I might as well give up” attitude.

Neither form of comparison is ideal in all situations, of course. Data suggest that for individuals who believe that they have little control over outcomes, mood enhancement that normally accrues with downward comparisons is diminished ( Buunk et al., 1990 ; Gibbons, 1999 ; Testa & Major, 1990 ) and even when downward comparisons do work to improve mood, they tend not to be potent motivators for change because they frame the challenge in terms of prior successes rather than in terms of one’s future goals. In contrast, because they are focused on what might be achieved, upward comparisons tend to foster more ambitious goals ( Collins, 1996 ; Croyle, 1992 ; Gibbons, 1999 ), and thus these tend to be the most useful in motivating all sorts of behaviors, including those related to health. But if our own progress toward an ambitious goal (influenced by the achievements of the person to whom we are comparing) seems to be stalled, discouragement can also result ( Buunk & Ybema, 1997 ; Van der Zee, Buunk, Sanderman, Botke, & van den Bergh, 2000 ). Thus, it is important that comparisons be made to those who are perceived as being at least somewhat similar to us. If we use as comparators individuals who are much more accomplished, our deficits will be highlighted and our progress is likely to seem sluggish or nonexistent—neither condition is useful in motivating ongoing efforts toward goal acquisition.

Social comparisons play an important role in our learning of behaviors, habits, and skills at all ages. And, although the process of social comparison changes and becomes more sophisticated with time, even young children employ this strategy. Conformity can occur without an overt comparison (see Hodges , this volume), but comparisons between self and important adults often result in mimicry for children, as they imitate the grown-up behaviors they see and parrot the words they hear. Many a parent has expressed amazement at the sponge-like quality of a child as she or he repeats a word that was not meant to be overheard or copies an expression that was supposed to pass unnoticed. Thus, it is not surprising that health behaviors, both good and bad, have their earliest roots in the home, influenced by family members.

Early Social Influences: Parenting and Family

The foundations of healthy (or unhealthy) behavior are typically shaped by parents and caregivers. Many health-relevant behaviors that are developed in childhood become fundamental aspects of one’s lifestyle—for example, dietary habits or exercise regimens—and there is growing consensus that important individuals in children’s lives should be incorporated into programs aimed at improving children’s health ( Davison & Birch, 2001 ). The habits and patterns that are developed in childhood, in turn, play an important role in the avoidance or development of chronic health problems such as cardiovascular disease or Type II diabetes. These lifestyle behaviors can be influenced either by direct instruction or by modeling (teaching by example) on the part of parents ( Tinsley, 1992 ), and data clearly suggest that both the health beliefs and the health behaviors of children are influenced by parental efforts (e.g., Jones, Steer, Rogers, & Emmett, 2010 ). One review of studies published between 1980 and 2002 demonstrated that parental modeling and involvement in both exercise and healthy eating had significant and long-lasting (beyond adolescence) effects on children’s behaviors and beliefs ( Norton, Froelicher, Waters, & Carrieri-Kohlman, 2003 ).

Direct instruction and reinforcement are effective means of molding and strengthening healthy behaviors and minimizing unhealthy ones. Although modeling tends to be effective over an extended developmental period, rules and direct encouragement tend to be more effective for children than for adolescents ( Pearson, Biddle, & Gorely, 2009 ).

In a large-scale community study of children, positive reinforcement for appropriate behaviors and monitoring of health-relevant behaviors were found to be associated with healthier eating and more exercise. On the other hand, parenting styles that were controlling in nature were found to be related to children’s poorer eating habits ( Arredondo et al., 2006 ). Similarly, a large cohort study found that encouraging healthy intake and physical activity were positively associated with energy balance and healthy body mass index (BMI).

Arredondo and colleagues also found, however, that the best approaches sometimes varied according to child characteristics (2006). For example, dietary monitoring and restriction were associated with desirable behaviors for children who ate normally but were less helpful for those who were characterized as picky eaters (willing to eat only a few food items) or as being always hungry compared with their peers ( Gubbels et al., 2011 ). The picky or hungry children did respond well to efforts that encouraged healthy food intake instead of restricting undesirable foods. This may be because they were not being pressured to cut down on foods that they liked but rather were encouraged to expand their food preferences, thus focusing on gains rather than losses. The results with picky and hungry children illustrate the importance of tailoring early parenting practices to the characteristics of the individual child, consistent with theory on the development of health behaviors within families (e.g., Birch & Davison, 2001 ).

Parental modeling of healthy behaviors can also be quite powerful ( Wrotniak, Epstein, Paluch, & Roemmich, 2005 ) and parental changes may predict similar changes in their children. For example, weight loss on the part of a parent has been shown to predict child weight loss ( Wrotniak, Epstein, Paluch, & Roemmich, 2004 ). In this analysis of data from three family-based obesity intervention programs, parental weight loss was an independent predictor of child weight loss—that is, despite whatever other behaviors the children were engaging in as part of their weight-loss regimen, they were more successful if their parent was also successful. This suggests that modeling facilitates goal achievement by processes somewhat different than simply changing behaviors in the shorter term by restricting foods or requiring adherence to an exercise program. This idea is consistent with the conclusions of Pearson and colleagues (2009) whose systematic review suggests that learning by observation or by watching someone model a behavior tends to be effective even after the more direct methods of instruction, monitoring, and encouragement have lost much of their power.

The strength of parental influence is also illustrated by studies showing that interventions aimed at improving children’s health behaviors might be most efficient when targeted specifically at parents, rather than at children or at parent–child dyads, which has in the past been the typical strategy. This type of parent-only intervention has been used to address problem behaviors such as tantrums, self-injury, phobias, and verbal aggression in children ( Johnson & Katz, 1973 ), and one literature review compared interventions in which children only, parents only, or a combination were targeted. This comparison found that when parents were exclusively targeted as the agents of change for their overweight children, three elements were improved: the obesogenic environment, health behaviors, and children’s weight ( Golan, 2006 ). In fact, targeting of parents shows even better outcomes than when both children and their parents attend sessions together ( Golan, Kaufman, & Shahar, 2006 ). The authors suggest that this may be partly due to the greater opportunity for indulgence and concession when more parties are involved in implementing changes, and they also posit that the lifestyle changes may feel more threatening to children (and they may be more likely to push back) when they are involved in this process that originates outside the family structure. Parent-only interventions are less burdensome and costly than more broadly targeted interventions ( Golan, Kaufman, & Shahar, 2006 ; Janicke et al., 2009 ) and, although some studies show no differences between approaches that involve or do not involve children (e.g., Boutelle, Cafri, & Crow, 2011 ; Munsch et al., 2008 ), the data taken as a whole suggest that focusing solely on parents may be ideal because results appear equivalent or better, with lower cost.

Social Influences in Adolescence: The Role of Peers and Friends

It has long been recognized that as children move into adolescence, the relative importance of peer groups for influencing some behaviors increases while the overt influence of parents tends to diminish ( Berndt, 1979 ; Lau, Quadrel, & Hartman, 1990 ). Self-evaluations regarding weight, attractiveness, and competence involve a great deal of social comparison, particularly at this developmental stage ( Eisert & Kahle, 1982 ; Jones, 2001 ; Mueller, Pearson, Muller, Frank, & Turner, 2010 ), and perceptions of the behaviors of their friends predict adolescents’ own behaviors ( Luszczynska, Gibbons, Piko, & Tekozel, 2004 ; Mueller et al., 2010 ). These perceptions have strong effects even when they are in error ( Prinstein & Wang, 2005 ). The relative “pull” of family versus peers has, however, been shown to vary both by individual and by behavior type. For example, an early review by Glynn (1981) found that, for alcohol use, the influences of peer and family groups were almost the same; for most illicit drugs, the family’s values were more important than those of peer groups; and, for marijuana use, peers were most influential. More recent research substantiates that the degree of influence wielded by a given person or social group does, indeed, vary according to the behavior type and characteristics of the individuals involved and highlights the complexity of these associations. Regarding characteristics of the target adolescent, a recent review finds that social isolation seems to be a particularly important risk factor for initiation of smoking ( Seo & Huang, 2012 ). With regard to the influence of others one longitudinal study of more than 2,500 adolescents indicated that parental expectations that their adolescent would not use alcohol not only predicted greater self-efficacy for avoiding alcohol but also less association with peers who used alcohol and lower self-reported use ( Nash, McQueen, & Bray, 2005 ). Another analysis of family and peer influences, this time of alcohol, cigarettes, marijuana, and other illicit drugs in a sample of over 4,200 7th–12th graders, confirmed that peer influences are generally quite important, as are parental attitudes and sibling behavior, with parent–child attachment being more weakly associated ( Bahr, Hoffman, & Yang, 2005 ). Interestingly, this study found that although parental attitudes and sibling substance use were related to the subject’s use of illicit drugs, their effects seem to be mediated almost entirely by peers. Finally, a recent assessment of the relative importance of parent and peer influences on intentions to smoke cigarettes found that parents initially hold more sway, but as the adolescent grows older, there is a shift. Parental influence declines over time, while peer influence strengthens ( Scalici & Schulz, 2014 ). Thus, parents would do well to discuss both risky and positive health behaviors with their children early and to provide as much guidance as possible in helping their children to select friends. These peers are likely to play an important role in influencing health behaviors—for better or for worse—and knowledge, a sense of self-efficacy for maintaining good health, and a set of like-minded friends may best facilitate long-term positive outcomes.

It is also prudent to note that not all data support the transition of influence from family to peer groups during adolescence. Researchers studying smoking behaviors in more than 3,800 6th–11th graders using a longitudinal design found different results from the standard cross-sectional design studies ( Chassin, Presson, Sherman, Montello, & McGrew, 1986 ). Specifically, they found that peer and family influences on smoking initiation were not significantly different in magnitude from one another between 6th and 11th grade. That is, these researchers failed to find evidence for the often-identified shift in relative influence from parents to peers during this period of life. A recent review (albeit containing many cross-sectional studies) does substantiate the shift in influence from parents to peers ( Mulvhill, 2014 ), but the literature as a whole highlights the great degree of complexity inherent in these associations. Other researchers also confirm that these associations are complex, with parental influences moderating those of peers, such as in the investigation of alcohol use during late adolescence ( Wood, Read, Mitchell, & Brand, 2004 ) and the indirect, protective effects of positive parenting against adolescent smoking ( Simons-Morton & Farhat, 2010 ).

Similar findings exist for positive health behaviors, such as physical activity and healthy eating. Significant others, including family members, friends, and classmates, were found to be important in shaping sports participation in a large sample of 10- to 15-year-olds, with peer influences being especially important for girls ( Keresztes, Piko, Pluhar, & Page, 2008 ). A review extended the latter finding for both boys and girls, and demonstrated that overweight youth were more active when they were with friends (regardless of the weight of the friends) than when they were alone or with family, and that physically active friends/peers increased children’s motivation to exercise ( Salvy, Bowker, Germeroth, & Barkley, 2012 ). This peer influence on exercise may be especially relevant to overweight adolescents, as indicated by another study. This work showed that although motivation to exercise and the actual distance biked were somewhat greater for all adolescents when they were in the presence of a friend or peer, the associations were statistically significant only for those who were overweight ( Salvy et al., 2009 ).

Another review also demonstrated the crucial role that friends play in determining the physical activity levels of adolescents ( Fitzgerald, Fitzgerald, & Aheme, 2012 ) with researchers identifying a variety of ways in which peer groups might exert their influence. These ways include the presence of and support from peers, the understood norms within peer groups, and the quality of the friendships themselves. An additional review similarly demonstrated that peer groups exert a meaningful influence on both physical activity and dietary intake for children and adolescents and suggested that peer networks be involved in intervention efforts ( Salvy, de la Haye, Bowker, & Hermans, 2012 ).

The importance of peer networks in enhancing adolescents’ health behaviors is echoed in the recommendations emerging from a study of the eating habits of more than 2,000 adolescents in 20 different schools in the Midwestern United States. Significant similarities were seen within groups of friends in the amount of whole grains, vegetables, and dairy products consumed, as well as for whether breakfast was eaten. This research suggests that health professionals should be encouraged to engage the friends of adolescents in interventions designed to improve dietary habits ( Bruening et al., 2012 ).

For young people coping with chronic health problems, incorporating peers and friends into the health management plan can be quite beneficial ( La Greca, Bearman, & Moore, 2002 ). These researchers found that effective maintenance of medical regimens is fostered when young patients affiliate with peers who engage in healthy behavior. Healthy peer groups can create a supportive environment in which the child or adolescent can more easily adapt to the challenges of his or her illness. Thus, whether a young person is dealing with chronic illness, developing health-related habits, or making decisions about high-risk behaviors, peer and friend networks appear to play an important role in facilitating good decision making and engagement in positive health behaviors.

Influences of Friends and Family in Adulthood

Social comparisons and peer behavior—real or perceived—are important not only to youth but also feature prominently in various ways throughout adulthood. As we shall examine later, the influence of peers can be harnessed to maximize positive health behaviors across all developmental periods.

The social influence of health-relevant behaviors often goes largely unrecognized by the individual, even as it is experienced. For example, social facilitation studies have often shown that more calories are consumed when an individual eats in the presence of others versus alone (e.g., de Castro & de Castro, 1989 ; Hetherington, Anderson, Norton, & Newson, 2006 ; Locher, Robinson, Roth, Ritchie, & Burgio, 2005 ), although some studies show that consumption is only increased when the others are familiar and not when the others are strangers (e.g., de Castro, 1994 ; Hetherington et al., 2006 ; Salvy, Howard, Read, & Mele, 2009 ). Most individuals are not aware of these changes in their eating behaviors.

The complexity of interactions between the social environment and behavior is highlighted, however, by impression management studies, which tend to show the opposite of what social facilitation studies find. The impression management studies suggest that individuals tend to decrease their food and/or calorie consumption in the presence of others (e.g., Roth, Herman, Polivy, & Pliner, 2001 ; Young, Mizzau, Mai, Sirisegaram, & Wilson, 2009 ), and this appears to happen most consistently among women who are eating with men. Researchers have used an “inhibitory norms” model to explain these seemingly contradictory sets of findings. They argue that when there are no clear signals of satiety, fullness, or satisfaction, individuals use social norms to determine when to stop eating. Consumption might increase or diminish depending upon the behavior of the comparison subjects and the desire of the individual to impress them; the behavior of others tends to suggest to the individual what his or her own behavior should be ( Herman, Roth, & Polivy, 2003 ; Wansink, 2006 ).

We often take hints from those around us when we are searching for cues to aid everyday decision making on topics ranging from littering to energy use to food choices. For instance, in Cialdini, Reno, and Kallgren’s now classic (1990) study, people were more likely to toss a flyer onto the ground when the area was already littered, indicating a social norm that littering was acceptable, than when the vicinity was trash-free. Similarly, women chose healthier snacks when healthy snack wrappers were visible, suggesting that other people had also chosen a healthy option ( Burger et al., 2010 ); and energy use decreased significantly when people were told that they used more energy than did others living in their neighborhood ( Schultz, Nolan, Cialdini, Goldstein, & Griskevicius, 2007 ). These tendencies are especially pronounced when we are unsure of how to act or truly do not know what option is best. But often social norms prove more influential than factual, objective information and operate even when we already know what we should do.

As an example, one study found that providing normative information on a simple sign (“Did you know? More than 90 percent of the time, people in this building use the stairs instead of the elevator. Why not you?”) decreased elevator use by nearly 50 percent in a 1-week period ( Burger & Shelton, 2011 ). Elevator use did not change at all when a sign with no normative data (“Did you know? Taking the stairs instead of the elevator is a good way to get some exercise. Why not try it?”) was in place. When we think about health and the many small health-related choices made each day, taking the stairs is a good illustrator of a small-scale behavior that, cumulatively, might make a real difference in a person’s fitness levels.

Consistent with data showing that social norms are used for decision making about individual behaviors, other studies illustrate that large-scale health outcomes are also linked to what those around us do. One finding that emerged from the Framingham Heart Study was that having a friend become obese during a given time period was linked to a 57 percent increase in the likelihood of an individual also becoming obese. Individuals were also more likely to become obese if their spouse (37 percent) or an adult sibling (40 percent) did ( Christakis & Fowler, 2007 ). This study strongly hints at the importance of social distance (as opposed to geographic distance), because altering the former changed the magnitude of the observed associations but changes in the latter did not—that is, similarities in outcomes were greater between individuals who were socially closer (e.g., close versus casual friends) but not who were geographically closer (e.g., next-door neighbors versus those living across town). The authors note that because of the time lag observed, the unimportance of geographic distance, and the control of baseline weight, explanations involving shared environmental exposures or genes are less likely than social explanations, and they suggest that changes in social norms seem more likely to be explanatory than processes of imitation. The researchers also posit that although social networks appear to play a role in the obesity epidemic, these same social phenomena might be channeled in ways that promote healthy behaviors. The same social influence that draws individuals into obesity with their friends and families might be used to draw them into exercise and healthy eating along with the important people in their lives. This strategy relies not only on social norms but also on social support.

Indeed, many studies have demonstrated the crucial role played by supportive social networks in the improvement and maintenance of a wide variety of health behaviors, including adherence to medical treatments (DiMatteo, 2004a , 2004b ); healthy eating ( Emmons, Barbeau, Gutheil, Stryker, & Stoddard, 2007 ; Ralston, Cohen, Wickrama, & Kwag, 2011 ); and exercising ( Emmons et al., 2007 ; Kouvonen et al., 2012 ), as well as positive health outcomes, including healthy aging ( Thanakwang & Soonthorndhada, 2011 ), management of hypertension ( Schmitz et al., 2012 ), and longer life ( House, Robbins, & Metzner, 1982 ; Tucker, Schwartz, Clark, & Friedman, 1999 ). The efficacy of incorporating social support and social connectedness into health interventions has also been demonstrated (e.g., Malchodi et al., 2003 ; Wing & Jeffery, 1999 ). The Framingham Heart Study, too, found that social influences apply not only to negative health outcomes (e.g., obesity) but also to positive behaviors—for example, a person’s chances of smoking decreased by 67 percent, if his or her spouse stopped, and also diminished if a friend or coworker quit ( Christakis & Fowler, 2008 ). The findings from the Framingham Heart Study are especially interesting because they suggest a blurring of the lines between two important forms of social influence: social norms and social support.

Social support is typically divided into the following subtypes: practical help (sometimes called “instrumental” or “tangible” support), informational support, and emotional support ( Wills, 1984 ). Tangible support is concrete in nature—someone driving you to your doctor’s appointment or giving you a ride to the gym so you do not miss your weightlifting class. Informational support, as its name implies, takes the form of shared information—someone recommending a safe biking trail or suggesting a new line of healthy snacks. Emotional support involves feelings and emotions—someone providing a listening ear and a shoulder to cry on, for example.

Social support takes different forms, and not all are equally beneficial when it comes to promoting health behaviors. For example, one study ( Kouvonen et al., 2012 ) found that for those who were, at baseline, already reporting appropriate levels of leisure-time physical activity, greater emotional support was related to continuation of the active behavior. But emotional support was not helpful in getting those who were not getting enough exercise to become more active. This study also showed, however, that practical support was associated with maintenance and with improvement of leisure-time physical activity rates over time, both for the already-active and for the more sedentary. The researchers did not comment on why emotional support failed to improve activity levels for the inactive, but it seems likely that the emotional support simply served to reinforce whatever was currently being done. For someone who was already active, emotional support would be reinforcing, but for someone who was not active, the implicit message may have been accepting of the status quo (e.g., “You’re fine just as you are, and you needn’t change a thing”).

An unsupportive network, not surprisingly, can be detrimental to the cultivation and maintenance of health behaviors. Intentionally or not, friends and family can enable and encourage bad habits or addictions, such as by continuing to buy sugary, processed desserts and storing them in cupboards shared with someone who is struggling to eat healthfully ( Freeman, 2001 ; Martin, Haskard-Zolnierek, & DiMatteo, 2010 ). Unsupportive behaviors (sometimes called “negative social support”) can also hinder coping, such as has been shown in patients with chronic obstructive pulmonary disease (COPD) who experience greater anxiety when they perceive that their social network members are insensitive or frequently let them down ( DiNicola, Julian, Gregorich, Blanc, & Katz, 2013 ).

It is not only unsupportive actions by members of the social network that may be harmful; specific supportive behaviors can have unpredictable outcomes as well. This same study found that practical support predicted greater anxiety in COPD patients—that is, patients with more support were also more anxious ( DiNicola et al., 2013 ). The authors suggest that although the association might be related to the relatively higher needs for support by patients who were more seriously ill (and relatedly more anxious), they speculated that the help patients received might also have served to highlight illness and dependence, thus increasing anxiety. Relatedly, a series of meta-analyses of partner support and smoking cessation found that when interventions to increase partner support were often ineffective and that when supportive partners provided “reminders” in the form of nagging or criticism, smokers were more likely to relapse and begin smoking again ( Park, Schultz, Tudiver, Campbell, & Becker, 2002 ; Park, Tudiver, & Campbell, 2012 ; Park, Tudiver, Schultz, & Campbell, 2004 ). The authors do not speculate about the process, but it seems likely that the poorer outcomes might be due to the desire to reassert a sense of personal control (i.e., reactance).

Particulars regarding the most beneficial form of support also differ according to demographics such as age and socioeconomic status—for example, two studies, one of nearly 8,000 adults and another of nearly 1,000, found that older individuals were more likely to prefer doing physical activity with people in their same age group, whereas similar-age activity partners were less important at younger ages ( Beauchamp, Carron, McCutcheon, & Harper, 2007 ; Burton, Khan, & Brown, 2012 ). Self-categorization, including concepts of being evenly matched, not conspicuous, and able to relate to one another are all suggested as possible explanations for the observed differences. The larger study ( Burton et al., 2012 ) also confirmed that low-income adults were more drawn to activities that were low-cost and offered benefit beyond exercise. This research highlights the importance of making physical activity affordable and multifunctional, particularly for lower income adults

Taken as a whole, these studies highlight the utility of tailoring health interventions so that they make use of social networks and support structures in ways that address the most pressing needs of particular groups or individuals.

Social Influence in Health Care

Friends and families influence our health both purposefully and inadvertently; yet it is within the health care system itself that the most overt influence over health is attempted. Health care providers (e.g., physicians, dentists, nurse practitioners) are expected to instruct and perhaps persuade. Modeling is an essential element as well; patients look to their health professionals for clues to healthy behavior.

Patients’ confidence in the advice and care they receive from their physicians has been shown to vary with the health of the physician himself or herself. For example, compared with patients of normal-weight physicians, those whose physicians are obese report less confidence in the health advice and illness-management counseling given to them ( Hash, Munna, Vogel, & Bason, 2003 ). Similarly, a study in which participants were randomly assigned to groups and then asked to rate physicians described as normal weight, overweight, or obese indicated that people were less trusting of, and less likely to follow the advice of, overweight or obese physicians; this was true regardless of the weight of the participant ( Puhl, Gold, Luedicke, & DePierre, 2013 ). This research suggests that a health care provider who does not model appropriate behaviors diminishes the influence she or he might have on patients. “Practicing what one preaches,” in the form of modeling effective health behaviors, is important.

A health care provider’s own health behavior tends to also predict the likelihood that he or she will actively promote better health in patients. Several studies have shown that physicians who are themselves healthier are more likely to counsel their patients about relevant health behaviors. For example, studies have found that physicians who exercised regularly and maintained a healthy weight were more comfortable counseling patients about healthy lifestyles than were those whose own lifestyles were less healthy ( Abramson, Stein, Schaufele, Frates, & Rogan, 2000 ; Howe et al., 2010 ; Livaudais et al., 2005 ).

This pattern was also demonstrated in a study that assessed nearly 500 physicians and found that only 18 percent of those who were overweight or obese talked to their patients about losing weight. On the other hand, 30 percent of those with a healthy BMI did so. Those with a healthy BMI also had greater confidence in their own abilities to provide advice on diet and exercise, and they felt that personal modeling of healthy weight-related behaviors, including regular exercise, was important ( Bleich, Bennett, Gudzune, & Cooper, 2012 ). Even health professionals whose personal behaviors do not represent the ideal should still counsel their patients about health lifestyles—they have expertise of various sorts, all of which can be important in helping patients to make good decisions, and they still have the ability to influence patients, although the data indicate that this ability is less than it might be if their personal behaviors more closely approximated their advice.

The concept of power has been important in health behavior—both research literature and practice—for a long time. French and Raven (1959) defined social power as the ability to exert social influence—that is, the ability to change the beliefs, attitudes, or behaviors of other people. They outlined six specific types of power, or ways in which these changes might be accomplished: (1) coercive power (derived from one’s ability to withhold rewards); (2) reward power (derived from one’s ability to provide rewards); (3) referent power (derived from one’s ability to make others feel valued and accepted); (4) legitimate power (derived from one’s position or status); (5) expert power (derived from one’s knowledge and experience); and (6) informational (derived from the persuasiveness of the specific content or information shared) ( Raven, 2010 ).

Information from a source that is deemed to have expertise on a particular topic carries more weight than the same information coming from a source that is perceived as less credible ( Cialdini, 2008 ). The power to influence often comes because of an individual’s knowledge and past experience (expert power), but health care professionals also use the other forms of power: coercive, reward, referent, informational, and legitimate. Referent power, in particular, is crucial when medical recommendations need to be internalized by patients ( Rodin & Janis, 1979 ) and is perhaps also especially relevant in situations where the health care provider’s own health behaviors are less than ideal. In these cases, sharing personal struggles and identifying with the patient might help him or her to feel more accepted, thus empowering him or her to make lifestyle changes despite the lack of modeling on the part of the provider ( Krupa, 2012 ).

Successfully influencing health behaviors using directives does not rely only on the expertise and power discussed earlier. Studies also show that messages are more persuasive when they come from someone who is well liked ( Cialdini, 2008 ). We tend to like people who we perceive as attractive ( Eagly, Ashmore, Makhijani, & Longo, 1991 ), with whom we are familiar ( Zajonc, 1968 ), and who we perceive as similar to us ( Byrne, 1971 ). Sharing some personal information (e.g., one’s own challenging but successful struggle to maintain an exercise regimen) may help in the latter two areas: helping patients to feel more connected to and similar to the health care provider who is making recommendations ( Martin et al., 2010 ).

Just as patients may be influenced in positive ways by the social processes noted earlier, expectations and biases may also negatively influence patient behavior. This tendency for expectations to become realities was outlined and labeled as the “self-fulfilling prophecy” phenomenon in the mid-20th century ( Merton, 1949 ) and numerous studies have since demonstrated that expectations—both negative and positive—can be quite powerful (e.g., Madon, Jussim, & Eccles, 1997 ; Rosenthal & Rubin, 1978 ; Snyder, 1992 ). In cases where the provider likes the patient or feels confident that she or he can carry out the prescribed behavior, this is not problematic. But when clinicians hold negative perceptions about their patients, subtle cues that encourage those patients toward less ideal behaviors may be conveyed. When trust and satisfaction with the clinical relationship are lacking, patients are less likely to adhere to treatment recommendations ( Bennett, Fuertes, Keitel, & Phillips, 2011 ; Hagiwara et al., 2013 ; Levesque, Li, & Pahal, 2012 ), but both satisfaction and health are greater when patients feel liked by their health care providers ( Hall, Horgan, Stein, & Roter, 2002 ). Patients’ trust and satisfaction levels, as well as the patient-centered behaviors displayed by their clinicians, have all been linked to the implicit biases held by clinicians (e.g., Cooper et al., 2012 ; Penner, Blair, Albrecht, & Dovidio, 2014 ; Penner et al., 2010 ). These studies highlight how important it is to pay attention to all forms of social influence, even those that can be easy to overlook.

When it comes to goal setting, health professionals are ideally positioned to help patients identify targets that are both palatable and manageable. Research shows that when people think about their goals as steps toward learning (versus indicators of performance), they are more likely to stay engaged in their pursuit of those aims, even when they experience setbacks ( Elliott & Dweck, 1988 ). Data also indicate that even small experiences of success, as well as perceptions of increasing task mastery, foster self-efficacy and encourage continued goal pursuit ( Stretcher, DeVillis, Becker, & Rosenstock, 1986 ; Stretcher et al., 1995 ). Health professionals can not only assist patients in setting reasonable goals that have a high likelihood of success, but they can also aid the framing of those goals—that is, helping patients to view goal setting as an opportunity for learning and improving skills, instead of as a measure of their ultimate success. In this way, health professionals are able to be potent forces for health behavior change.

Health professionals may also be in a unique position to connect patients with appropriate support groups that can then influence their health outcomes in a variety of ways. In such groups, patients may experience multiple gains ( Martin et al., 2010 ): emotional support to help them stay engaged in the process of self-care or behavior change; they may find practical advice and ideas for overcoming the obstacles they encounter; and they may be empowered as they help others who are struggling in areas where they have experienced success. Although the concepts of support groups and peer communities are not new, their movement into the digital realm is still in progress. These groups are varied—from discussion groups and chat rooms to newsfeeds and voice-activated systems; and they are often part of a complex system of care delivery. These methods have emerged recently, and there has not yet been much systematic evaluation of these virtual communities. One detailed review of outcomes associated with various sorts of e-groups concluded that while they do not appear to be harmful, neither do they seem to improve health outcomes ( Eysenbach, Powell, Englesakis, Rizo, & Stern, 2004 ). Most of the studies included elements other than peer-to-peer support, and therefore it was impossible to determine whether intervention effects were due to the group or to some other element of the overall program. Another meta-analysis (this one focused specifically on depression as the outcome) drew similar conclusions and indicated that studies that were not as well designed (e.g., no control group) were more likely to find an association between the online support group and the measured outcome ( Griffiths, Calear, & Banfield, 2009 ). Some studies have found that participation rates in e-groups is higher than with in-person groups ( Alemi et al., 1996 ) and satisfaction also seems to be high ( Hoey, Ieropoli, White, & Jefford, 2008 ), but links to other outcomes, including psychosocial, are inconsistent. Considering these factors, the best practice might be to have a variety of groups—of both types—available for patients, and for health care providers to help guide them to the environments that best meet their needs.

Influence of Larger Social Systems

The focus thus far has been primarily on individual relationships, or social influence in relatively small groups. Larger societal systems, however, also influence personal behaviors, although not always as efficiently as we might guess. Public health programs aim to change health behaviors by educating and motivating people toward ideal behaviors. Educational interventions such as 5-A-Day for Better Health ( Frazao, 1999 ) and the Nutritional Labeling and Education Act ( Marcus, Owen, Forsyth, Cavill, & Fridinger, 1998 ) have demonstrated moderate successes. Over a 5-year period the number of adults meeting the 5-a-day goal increased slightly, as did the number of adults who reported reading nutritional labels ( French, Story, & Jeffery, 2001 ). There is no evidence, however, of a strong link between educational strategies such as these and large-scale behavior change in the population ( Brownson, Baker, Housemann, Brennan, & Bacak, 2001 ).

Health-related media campaigns have historically received free time slots for their public service announcements (PSAs), but free access has diminished over time, and now it is common to have these sorts of informational and motivational messages funded by governmental agencies, nonprofit health organizations, or even for-profit providers. One of the early successes in this area was the Stanford heart disease prevention project in which communities targeted with intensive media campaigns showed improvements in cardiovascular health ( Farquhar et al., 1977 ). This success fueled an increase in subsequent media campaigns, but their degrees of success have varied.

A review of mass-media health campaigns ( Snyder & Hamilton, 2002 ) found that about 7–10 percent more people in target (versus control) communities change their behaviors and the changes are greater when adoption of a new behavior, rather than the cessation of an already-established behavior, is targeted. A subsequent review, utilizing both meta-analyses and other literature found an effect of about 5 percent in intervention communities ( Snyder, 2007 ).

Because many mass-media campaigns are minimally effective (perhaps because they are too obvious in their attempts to sway perceptions or behaviors; Murphy, Hether, & Rideout, 2008 ), embedding of these messages into regular entertainment media is becoming more common, analogous to the “product placement” that has expanded dramatically over recent years. This approach was pioneered by Miguel Sabido of Mexico in the 1970s in an effort to improve adult literacy. Albert Bandura himself was impressed with Sabido’s application of Bandura’s social cognitive theory and the approach is now used around the world to educate people and connect them with community resources ( Smith, 2002 ). One early example in the United States was the storyline for the television soap opera The Bold and the Beautiful in which one of the characters confided to his long-term girlfriend that he was HIV-positive. This episode, which had been planned in collaboration with scientists from the Centers for Disease Control and Prevention (CDC), was designed to challenge stereotypes associated with HIV and to encourage viewers to get tested. It was estimated by Neilsen that approximately 4 million viewers tuned in and received this message ( Kennedy, O’Leary, Beck, Pollard, & Simpson, 2004 ), and calls to the National STD and AIDS Hotline increased dramatically following its airing in the summer of 2001. Subsequently, the CDC partnered with the University of Southern California’s Annenberg School for Communication to form Health, Hollywood, and Society , which aimed to provide accurate information to television writers for embedding into storylines ( Kennedy, Murphy, & Beck, 2004 ). Health, Hollywood, and Society contributes to hundreds of health-related storylines each year ( Dutta, 2007 ). Because of their broad reach, and their appealing format, these types of social influences hold a good deal of promise; because of their nature, however, their specific impacts are challenging to parse in experimental studies and more study of the long-term effects of such campaigns is needed.

The use of social influence processes holds a good deal of promise in fostering health behavior, in individuals as well as in populations. The influence of family members, friends, peers, and even perceived others can be harnessed to maximize positive health behaviors across all developmental periods. The specific effects of social support and social influence are, in some areas, challenging to determine precisely in observational studies; experimental studies are emerging to support the long-term effects of social influence, and more experimental intervention research is needed.

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Essays on Social Influence

Abstract: This dissertation explores various aspects of social influence processes in political behavior research. Specifically, three separate essays explore the ways in which communication, social conformity, cultural transmission, and other interpersonal influence processes operate to generate similar public behaviors among groups of interconnected individuals.

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tices aimed at increasing the likelihood that people will comply with requests, persuasion and suggestion they are addressed with. It describes sequential techniques (foot-in-the-door, door-in-the-face, foot-in-the-face, low ball) as well as techniques based on cognitive mechanisms (that’s not all, even a penny helps, dialogue involvement) or on emotional mechanisms (induction of guilt, embarrassment, fear-then-relief). The paper also presents examples of using the above mentioned techniques with special focus on some which were taken from political life.

American Economic Journal: Microeconomics

Andrea Mattozzi

Political Communication

Dhavan Shah

Political …

Matthew Nisbet

Meciad Meriem

International Journal of …

Michael Huge

SSRN Electronic Journal

The Pacific Sociological Review

Lynn Smith-Lovin

Jason Jones

Cansu Parlak

It has been supported by studies that early experiences of political choices affect individuals' later lives. In order to explain how the political awareness of individuals develops, socialization in childhood and adolescence was modeled, and the attitudes of children towards different ethnic groups were evaluated. It has been problematized that individuals inherit their political views from their parents, and it has been determined that this situation also affects their adult lives. Whether or not the political tendencies of pre-adult individuals will be stable has been evaluated by comparing partisan discourses and partisan information. The effects of political conflicts and external political events on the political socialization of individuals were discussed, and the necessity of relative deprivation as a trigger/cause of social movements was questioned.

Social Influence Topic Essays for AQA A-Level Psychology

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Social influence essay.

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Social influence is the process by which individuals make real changes to their feelings and behaviors through interaction with others who are perceived to be similar, desirable or expert. Current research on social influence falls into five main areas: (1) minority influence, (2) research on persuasion, (3) Dynamic Social Impact Theory, (4) a structural approach to social influence, and (5) Expectation States Theory.

Minority influence occurs when a minority subgroup attempts to change the majority. While some research has characterized the process of social influence as the majority riding roughshod over the minority, many scholars interested in minority influence believe that every member of a group can influence others.

Current research on persuasion, defined as change in attitudes or beliefs based on information received from others, focuses on messages sent from source to recipient. This research assumes that individuals process messages carefully whenever they are motivated and able to do so.

Dynamic Social Impact Theory describes and predicts the diffusion of beliefs through social systems. In this view, social structure is the result of individuals influencing each other in a dynamic and iterative way and society is a system in which individuals interact and impact each others’ beliefs.

The structural approach to social influence examines interpersonal influence that occurs within a larger network of influences. Social influence here is the process by which a group of actors will weigh and then integrate the opinions of others.

Expectation States Theory provides another formal treatment of social influence. When group members are initially unequal in status, inequalities are imported to the group from the larger society such that, for example, age structures a hierarchy of influence.

Bibliography:

• Friedkin, N. (1998) A Structural Theory of Social Influence. Cambridge University Press, Cambridge.
• Moscovici, S., Mucchi-Faina, A., & Maass, A. (eds.) (1994) Minority Influence. Nelson-Hall, Chicago, IL.
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Social influence – NYT Mini crossword clue answer May 29 2024

The “social influence” clue in the NYT Mini Crossword refers to a common online influence. I figured it out when I thought of popular streamers and players who thrive on internet fame. Here are some hints to help you with this part of the May 29, 2024 puzzle.

Social influence NYT Mini hints and answer

Hint 1: meaning.

Power and influence over something or someone.

Hint 2: First and last letters

The answer starts with “ C ” and ends with “ T “.

Hint 3: Anagram

It’s an anagram of “ OCTUL “.

Hint 4: Sounds like…

The answer sounds similar to “ clot ” and “ cloud “.

The answer to “social influence” in 4A is CLOUT .

All answers to the NYT Mini Crossword of May 29, 2024

• 1A Business whose hires usually work out – GYM
• 4A Social influence – CLOUT
• 6A Difficult item for a mover – COUCH
• 7A Defeat soundly, in slang – SMOKE
• 8A View from an airplane window – SKY
• 1D Latches (onto) – GLOMS
• 2D “Everything good?” – YOUOK
• 3D Full of mud and gunk – MUCKY
• 4D Includes on an email, for short – CCS
• 5D “___ nerve!” – THE

I solved it! What’s next?

If you want to play past Mini Crossword puzzles, you can do so via the New York Times puzzles archive if you’re a subscriber. Otherwise, you can try the LA Times Mini or the Daily Mini on Washington Post .

If you want more of the NYT Mini , you’ll have to wait until 9pm CT today for access to tomorrow’s puzzle. Changing your device’s date and time to the next day won’t unlock the puzzle.

If you’re looking for a bigger challenge, you can also take on full-sized crosswords available on various websites. The New York Times Crossword, however, is locked behind a subscription. You can find a free syndicated version in several other newspapers online. This simply means it’s a puzzle the NYT released five to six weeks ago to its subscribers. If you haven’t solved it yet, it’s still a fresh new puzzle for you, and that’s what really matters.