how to write a literature review using chatgpt

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Step-by-Step Guide: How to Use ChatGPT to Write a Literature Review With Prompts

Step-by-Step Guide: How to Use ChatGPT for Writing a Literature Review

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A step-by-step guide: how to use chatgpt for writing a literature review, chatgpt prompts to write a literature review.

Writing a literature review can be a challenging task for researchers and students alike. It requires a comprehensive understanding of the existing body of research on a particular topic. However, with the advent of advanced language models like ChatGPT, the process has become more accessible and efficient.

In this step-by-step guide, ilovephd will explore how you can leverage ChatGPT to write a compelling literature review that is both informative.

Step 1: Defining Your Research Objective Before diving into the literature review process, it is crucial to define your research objective.

Clearly articulate the topic, research question, or hypothesis you aim to address through your literature review. This step will help you maintain focus and guide your search for relevant sources.

Step 2: Identifying Keywords and Search Terms To effectively use ChatGPT to assist in your literature review, you need to identify relevant keywords and search terms related to your research topic.

These keywords will help you narrow down your search and gather pertinent information. Consider using tools like Google Keyword Planner or other keyword research tools to discover commonly used terms in your field.

Step 3: Familiarizing Yourself with ChatGPT Before engaging with ChatGPT, it is essential to understand its capabilities and limitations. Familiarize yourself with the prompts and commands that work best with the model.

Keep in mind that ChatGPT is an AI language model trained on a vast amount of data, so it can provide valuable insights and suggestions, but it’s important to critically evaluate and validate the information it generates.

Step 4: Generating an Initial Literature Review Outline Start by creating an outline for your literature review. Outline the main sections, such as the introduction, methodology, results, discussion, and conclusion.

Within each section, jot down the key points or subtopics you want to cover. This will help you organize your thoughts and structure your review effectively.

Step 5: Engaging with ChatGPT for Research Assistance Once you have your outline ready, engage with ChatGPT for research assistance.

Begin by providing a clear and concise prompt that specifies the topic, context, and any specific questions you have. For example, “What are the current trends in [your research topic]?” or “Can you provide an overview of the main theories on [your research question]?”

Step 6: Reviewing and Selecting Generated Content ChatGPT will generate a response based on your prompt. Carefully review the content generated, considering its relevance, accuracy, and coherence.

Extract key points, relevant references, and insightful arguments from the response and incorporate them into your literature review. Be sure to cite and attribute the sources appropriately.

Step 7: Ensuring Coherence and Flow While ChatGPT can provide valuable content, it’s important to ensure the coherence and flow of your literature review.

Use your critical thinking skills to connect the generated content with your research objective and existing knowledge. Rearrange, rephrase, and expand upon the generated text to ensure it aligns with the structure and purpose of your review.

Step 8: Editing and Proofreading Once you have incorporated the generated content into your literature review, thoroughly edit and proofread the document.

Check for grammatical errors, consistency in referencing, and overall clarity. This step is crucial to ensure your literature review is polished and professional.

Prompts you can use when engaging with ChatGPT for research assistance in writing a literature review:

• “Can you provide an overview of the main theories and concepts related to [your research topic]?”
• “What are the current trends and developments in [your research field]?”
• “Can you suggest some key studies or research papers on [specific aspect of your research topic]?”
• “What are the main methodologies used in conducting research on [your research topic]?”
• “Can you provide a critical analysis of the existing literature on [your research question]?”
• “Are there any gaps or areas of controversy in the literature on [your research topic] that need further exploration?”
• “What are the key findings and conclusions from the most recent studies on [your research topic]?”
• “Can you suggest some reputable journals or publications explore for relevant literature in [your research field]?”
• “What are the different perspectives or schools of thought in the literature on [your research topic]?”
• “Can you provide a summary of the historical background and evolution of research on [your research topic]?”

Remember to provide clear and specific instructions in your prompts to guide ChatGPT in generating relevant and accurate content for your literature review.

Using ChatGPT to write a literature review can greatly facilitate the research process. By following a step-by-step approach, researchers can effectively leverage ChatGPT’s capabilities to gather insights, generate content, and enhance the quality of their literature review. However, it is important to approach the generated content critically, validate it with reliable sources, and ensure coherence within the review.

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How To Use ChatGPT To Write A Literature Review: Prompts & References

In the rapidly evolving world of academic research, the integration of AI tools like ChatGPT has transformed the traditional approach to literature reviews. As a researcher, you should also leverage on this tool to make your research work easier.

In this post, explore how ChatGPT can enhance the literature review process. We’ll explore how specific prompts can effectively guide this advanced AI model to generate insightful content, while ensuring accuracy, relevance, and academic integrity in their scholarly work.

How to Use ChatGPT for Writing a Literature Review

Understanding chatgpt’s limitations.

While it can efficiently generate content, streamline the research process, and provide a comprehensive understanding of relevant literature, its capabilities are not without constraints. Here are some for you to consider:

Dependence On Pre-Existing Datasets

Since ChatGPT is a language model trained on available data, it may not include the most recent research papers or cutting-edge findings in a specific field. This gap can lead to a lack of current state-of-research insights, particularly crucial in fields like technology and science where advancements happen rapidly.

May Lack Depth And Context

ChatGPT, while able to produce summaries and synthesize information, might not fully grasp the nuanced arguments or complex theories specific to a research topic. This limitation necessitates that researchers critically evaluate and supplement AI-generated text with thorough analysis and insights from recent systematic reviews and primary sources.

Risk Of Plagiarism

Although ChatGPT can generate human-like text, it’s vital to ensure that the content for your literature review is original and properly cited. Relying solely on ChatGPT to write a literature review defeats the purpose of engaging deeply with the material and developing a personal understanding of the literature.

Not A Total Replacement of A Researcher

While ChatGPT can assist non-native English speakers in crafting clear and concise academic writing, it’s not a replacement for the human ability to contextualize and interpret research findings. Researchers must guide the AI model with specific prompts and leverage it as a tool rather than a substitute for comprehensive analysis.

By keeping these limitations in mind, ChatGPT can be a valuable aid in the literature review process, but it should be used judiciously and in conjunction with traditional research methods.

Defining Research Objective

When starting on writing a literature review, the initial step involves using ChatGPT to define your research question or hypothesis.

The AI model’s ability to respond with a summary of the current state of research in your field can provide a comprehensive understanding, especially for systematic reviews or research papers.

For example, by inputting a prompt related to your research topic, ChatGPT can generate human-like text, summarizing prior research and highlighting relevant literature.

One insider tip for effectively using ChatGPT in the literature review process is to leverage its natural language processing capabilities to identify relevant keywords.

These keywords are crucial for non-native English speakers or those new to a research field, as they streamline the search for pertinent academic writing. Additionally, ChatGPT can guide you in understanding the context of your research topic, offering insights that are often challenging to find.

Using AI language models like ChatGPT for generating content for your literature review is efficient and effective, saving valuable time. However, it’s vital to critically evaluate the generated text to ensure it aligns with your research objectives and to avoid plagiarism.

ChatGPT’s ability to synthesize large amounts of information can aid in developing a clear and concise outline, but remember, it’s a guide, not a replacement for human analysis.

Despite these limitations, ChatGPT provides a unique advantage in conducting literature reviews. It can automate mundane tasks, allowing researchers to focus on analysis and critical thinking.

Identifying Keywords and Search Terms

Using ChatGPT to identify relevant keywords related to your research topic can significantly streamline your workflow.

For instance, when you input a summary of your research question into ChatGPT, the AI model can generate a list of pertinent keywords.

These keywords are not just randomly selected; they are based on the vast amounts of information in ChatGPT’s dataset, making them highly relevant and often inclusive of terms that are current in your research field.

An insider tip for leveraging ChatGPT effectively is to guide the AI with clear and concise prompts.

For example, asking ChatGPT to: “summarize key themes in [specific field] research papers from the last five years” can yield a list of keywords and phrases that are not only relevant but also reflective of the current state of research.

This approach is particularly beneficial for conducting systematic reviews or for non-native English speakers who might be unfamiliar with specific academic jargon.

While ChatGPT can provide a comprehensive understanding of relevant literature and help automate the identification of keywords, it’s important to critically evaluate the generated content.

Researchers should use ChatGPT as a tool to augment their research process, not as a replacement for human insight.

It’s crucial to mind the limitations of the AI model and ensure that the keywords identified align with the research topic and objectives.

Creating an Initial Literature Review Outline

The key to using ChatGPT effectively in crafting an initial outline lies in its ability to generate content based on specific prompts.

For instance, a researcher working on organic photovoltaic devices can input a prompt into ChatGPT, such as “Help me create a structure for a literature review on organic photovoltaic devices.”

The AI model, using its comprehensive understanding of the research topic, can then produce a preliminary structure, including sections like:

• Introduction
• Advances in materials and technology, performance, and efficiency.

This generated outline serves as a valuable starting point. It helps in organizing thoughts and determining the key areas that the literature review should cover. I

mportantly, researchers can refine and expand this initial outline as they delve deeper into their topic, ensuring it aligns with their specific research question and the current state of research.

However, while ChatGPT can streamline the review process and save valuable time in creating an initial outline, researchers should not solely rely on it.

The content generated by ChatGPT must be critically evaluated and supplemented with in-depth research. This involves:

• Reading systematic reviews
• Reading research papers, and
• Summarizing relevant literature to ensure the review is comprehensive and up-to-date.

Get ChatGPT To Help You During Research, Using The Right Prompts

The key to effectively using ChatGPT in this process lies in crafting the right prompts, guiding the AI to generate relevant and useful content. 

When initiating a literature review, the prompt should aim for a broad understanding of the research topic. For instance, asking ChatGPT to:

• “Give a brief overview of research done on [topic]”
• “What are some of the recent findings on the [topic] in research?” or 
• “Summarize the historical development of [topic] in academia”

Helps in capturing the general landscape of the field. These prompts assist in identifying key theories, methodologies, and authors within the research area. As the review progresses, more specific prompts are necessary to delve deeper into individual studies. Queries like:

• “Summarize the main arguments and findings of [specific paper]” or
• “What are the strengths and weaknesses of [specific paper]?”

enable ChatGPT to provide detailed insights into particular research papers, aiding in understanding their contribution to the broader field. Comparative prompts are also crucial in synthesizing information across multiple works. Asking ChatGPT to:

• “Compare and contrast the methodologies of [paper 1] and [paper 2]” or
• “How do the findings of [paper 1] and [paper 2] agree or disagree?”

helps in discerning the nuances and disparities in the literature. In the final stages of the literature review, prompts should focus on summarizing findings and identifying emerging trends or gaps. For example:

• “What trends or patterns have emerged from the literature on [topic]?” or
• “What future research directions are suggested by the literature on [topic]?”

We will share more on these ChatGPT prompts in the later part of this post, read on.

Reviewing ChatGPT’s Responses

When using ChatGPT to write a literature review, it’s crucial to critically evaluate its responses.

Firstly, researchers should cross-reference the information provided by ChatGPT with actual research papers.

This step ensures the accuracy of the data and helps in identifying any discrepancies or outdated information, given that ChatGPT’s dataset may not include the most recent studies.

Another essential aspect is assessing the coherence and depth of the AI-generated text. ChatGPT can summarize and synthesize information efficiently, but it might not capture the nuances of complex theories or research arguments.

Researchers should ensure that the content aligns with their research question and systematically reviews the topic comprehensively. This is where a researcher’s value comes in.

Additionally, verifying the originality of the content is vital to avoid plagiarism. While ChatGPT can generate human-like text, researchers must ensure that the AI-generated content is used as a guide rather than a verbatim source. 

Proper citations and references are essential to maintain the integrity of the literature review. Avoid torpedoing your own research by committing plagiarism.

Ensuring Coherence and Flow

One of the challenges when using such advanced AI language models is ensuring the coherence and flow of the final document. This aspect is crucial as it determines the readability and academic rigor of the literature review.

ChatGPT can generate vast amounts of content on a wide range of topics, responding efficiently to prompts and synthesizing information from its extensive dataset.

However, the content generated by ChatGPT, while informative, might not always align seamlessly with the specific research question or maintain a consistent narrative flow.

To tackle this, researchers need to take an active role in guiding ChatGPT and subsequently refining its output.

A practical approach is to use ChatGPT as a starting point, leveraging its ability to quickly provide summaries, synthesize relevant literature, and identify key references and keywords related to the research topic. For example, prompts like:

• “Summarize the current research on [topic]” or
• “Identify key debates in [topic]”

Can yield valuable initial insights.

Once this foundational information is obtained, the crucial task is to carefully review and edit the AI-generated content.

This involves connecting the dots between different sections, ensuring that each part contributes meaningfully to addressing the research question, and refining the language to maintain academic standards.

It’s also essential to check for and avoid plagiarism, ensuring that all sources are correctly cited.

In addition, considering the vast amounts of information ChatGPT can access, it’s vital to verify the accuracy and relevance of the content.

Researchers should cross-reference AI-generated summaries with actual research papers, especially the most recent ones, as ChatGPT’s dataset may not include the latest studies.

Editing and Proofreading

Now that your literature review is mostly written out, now focus on the editing and proofreading. The content generated by ChatGPT needs to be meticulously reviewed and edited. Here are the steps:

• Verifying the accuracy of the information. Researchers must cross-check the AI-generated content against actual research papers and systematic reviews. This ensures that the latest studies are accurately represented.
• Improve coherence and flow. Researchers should restructure sentences, ensure logical progression of ideas, and maintain a consistent academic tone throughout the document.
• Checking for plagiarism. Despite ChatGPT’s ability to generate human-like text, researchers must ensure that all sources are correctly cited and that the review does not inadvertently replicate existing material.
• Check Grammar and Spelling: Editing should encompass grammar checks, vocabulary refinement, and ensuring that the language used is appropriate for an academic audience.
• Update Citation: Review citation, or reference list to ensure everything is cited correctly, and the citation list is written out to your required standard, be it MLA, Chicago, or APA.

What ChatGPT Prompts To Use When Writing A Literature Review?

There are many ways to use ChatGPT to write literature review, usually by using the right prompts. Here’s how specific types of prompts can be effectively employed, with multiple examples for each category:

• “Provide a comprehensive overview of the latest research on [topic].”
• “Summarize the current understanding and key findings in the field of [topic].”
• “Detail the dominant theoretical frameworks currently used in [topic].”
• “Describe the evolution of theoretical approaches in [topic] over the past decade.”
• “Identify and discuss the major debates or controversies in [topic].”
• “What are the conflicting viewpoints or schools of thought in [topic]?”
• “List the leading researchers in [topic] and summarize their key contributions.”
• “Who are the emerging authors in [topic], and what unique perspectives do they offer?”
• “Explain the most common research methodologies used in studies about [topic].”
• “How have the methodologies in [topic] research evolved recently?”
• “Trace the historical development and major milestones in [topic].”
• “Provide a timeline of the key discoveries and shifts in understanding in [topic].”
• “What significant paradigm shifts have occurred in [topic] in the last twenty years?”
• “How has the focus of research in [topic] changed over time?”
• “Analyze the methodology and conclusions of [specific paper].”
• “Discuss the impact and reception of [specific paper] in the field of [topic].”
• “Compare the results and methodologies of [paper 1] and [paper 2] in [topic].”
• “How do [paper 1] and [paper 2] differ in their approach to [topic]?”
• “Based on current literature, what are the suggested future research directions in [topic]?”
• “Identify gaps in the literature of [topic] that could be explored in future studies.”

By using these types of prompts, researchers can guide ChatGPT to produce content that is not only relevant to their literature review but also rich in detail and scope.

Wrapping Up: Use Other AI Tools Too, Not Just ChatGPT

In conclusion, while ChatGPT serves as a powerful ally in the literature review process, it’s important to recognize it as one of many AI tools available to researchers as well. Diversifying your AI toolkit can enhance the depth and breadth of your review, offering varied perspectives and methodologies.

As AI continues to evolve, embracing a range of these tools can lead to more comprehensive, nuanced, and innovative academic writing, expanding the horizons of research and scholarly exploration beyond what we currently envision.

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

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Step 1: title and title page creation by chatgpt, step 2: abstract/summary creation by chatgpt, step 3: introduction creation by chatgpt, step 4: can chatgpt create a literature review, step 5: can chatgpt assist in brainstorming the methodology of studies, step 6: do not use chatgpt for fabricating patient data or results, step 7: discussion and conclusions, step 8: references, disadvantages of using chatgpt in research, acknowledgment., chatgpt for research and publication: a step-by-step guide.

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Som S. Biswas; ChatGPT for Research and Publication: A Step-by-Step Guide. The Journal of Pediatric Pharmacology and Therapeutics 1 October 2023; 28 (6): 576–584. doi: https://doi.org/10.5863/1551-6776-28.6.576

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This commentary provides a concise step-by-step guide on using ChatGPT, an advanced natural language processing (NLP) model, for research and publication purposes. The guide assesses crucial aspects, including data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations. By addressing challenges related to biases, interpretability, and plagiarism, this commentary offers insights and recommendations for the responsible and ethical use of ChatGPT. The guide empowers researchers to ethically integrate ChatGPT effectively into their workflows, enhancing productivity and improving the quality of their scientific publications. Through clear instructions and guidelines, researchers can tap into the transformative potential of ChatGPT, driving scientific progress in a language-driven world.

In recent years, the field of NLP has witnessed remarkable advancements, bringing us closer to the realm of humanlike language generation. Among these advancements, ChatGPT, based on the groundbreaking GPT-3.5 architecture developed by OpenAI, stands as an impressive language model capable of generating coherent and contextually relevant text responses. With its ability to understand and respond to user inputs, ChatGPT has opened up new possibilities for various applications, including research and publication. 1 – 3  

The traditional process of conducting research and publishing scientific papers has been significantly transformed by the emergence of ChatGPT. Researchers and authors can now leverage the power of this sophisticated language model to streamline and enhance their workflow, leading to improved efficiency and higher-quality publications. However, using ChatGPT effectively in the research and publication domain requires a comprehensive understanding of its capabilities, limitations, and best practices.

In this commentary I offer my thoughts for a step-by-step guide for researchers and authors who seek to harness the potential of ChatGPT in their research endeavors and publication efforts. By exploring various aspects, such as data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations, this guide will equip researchers with the necessary knowledge to harness the full potential of ChatGPT in their scientific pursuits. Moreover, this commentary will delve into the challenges associated with using ChatGPT for research and publication, including biases, interpretability, and concerns regarding plagiarism. By addressing these challenges directly, I aim to provide researchers with valuable insights and recommendations to navigate these important issues and ensure the responsible and ethical use of ChatGPT as a research tool. 4  

The significance of my guide lies in its potential to bridge the gap between the rapid progress of language models like ChatGPT and the research and publication process. By elucidating the intricacies of integrating ChatGPT into scientific workflows, researchers will be empowered to leverage this advanced technology effectively, thereby enhancing the overall quality and impact of their research output. 5   In the following sections, I present a comprehensive overview of the steps involved in using ChatGPT for research and publication.

ChatGPT can be a valuable tool in generating titles for research papers. Its ability to understand and generate humanlike text allows it to analyze and synthesize information provided by researchers to craft concise and impactful titles. By leveraging its vast knowledge base and language capabilities, ChatGPT can assist in capturing the essence of a research paper, conveying the main focus and contributions succinctly. Researchers can collaborate with ChatGPT by providing relevant information, such as the subject, objectives, methodology, and key findings of their study. ChatGPT can then generate multiple title options, offering different perspectives and angles that researchers can consider. This collaboration with ChatGPT can save time and stimulate creativity, helping researchers refine their titles to accurately represent their work and engage potential readers. ChatGPT can then be used to create the entire title page and then can also customize based on each journal’s recommendations.

For example:

Thus, we see that ChatGPT can write an entire title page based on just the title and author details. We notice that ChatGPT has created an email address that is incorrect and needs manual rectification. However, the rest of the title page, including keywords and the running title, is appropriate.

ChatGPT can assist in condensing complex information into a clear and engaging abstract/summary, helping researchers communicate the significance and novelty of their research to a wider audience. By leveraging the language proficiency of ChatGPT, researchers can save time and effort in crafting abstracts while ensuring that the key aspects of their study are accurately represented.

In this example, we demonstrate that ChatGPT can create an entire abstract just by using the title alone. However, the more information researchers provide (preferably the entire body of the paper should be entered into chatGPT), the more accurate the abstract becomes.

By collaborating with ChatGPT, researchers can provide key information, such as the background, significance, and objectives of their study. ChatGPT can then generate a well-structured introduction that sets the context, highlights the relevance of the research, and outlines the paper’s objectives. Also, ChatGPT can be used to generate keywords and generate an abbreviations list from the article by using prompts. However, it is important to note that the generated introduction should be reviewed, customized, and refined by the researchers to align with their specific study and writing style.

In the example below, we note that ChatGPT has not only created an introduction but also the objectives of the study, which can then be edited by the human author.

Yes, ChatGPT can help generate a literature review, but it is important to note that it may not have access to the most up-to-date research articles and studies due to copyrights and limited access to some journals. Additionally, a literature review typically requires a comprehensive analysis of multiple sources, so the generated response may not cover all relevant studies. Nonetheless, it can assist in providing a basic literature review on a given topic, which will need human authors to add to and edit it.

As we can see, ChatGPT is not as good at giving a detailed review of the literature as it is at summarizing contents or creating an introduction. Thus, its use is limited, if there is any at all, in this section of the paper.

ChatGPT can be a helpful tool in conceptualizing the methodology for research papers. By engaging in a conversation with ChatGPT, researchers can discuss their research objectives, study design, data collection methods, and data analysis techniques. ChatGPT’s natural language understanding allows it to provide suggestions and insights based on its knowledge base and understanding of research methodologies. Although ChatGPT can assist in generating ideas and providing guidance, it is important for researchers to critically evaluate and adapt the suggestions to align with their specific research goals and requirements.

Although the methodology is something that is unique to each paper and needs a human researcher to conceptualize it, we see in this example that ChatGPT can assist by giving ideas and examples based on the input of the title by the human researcher. Thus, ChatGPT can be part of brainstorming sessions when conceptualizing a study, although this section needs significant editing by a human, unlike the introduction or summary.

This section of the paper must be authentic, and ChatGPT has a limited role, if any, because patient data have to be original. ChatGPT also currently cannot analyze clinical data compared with statistical software, like SPSS Statistics and Base SAS. However, Microsoft appears to be developing an Excel copilot that uses AI to create graphs and plots, and its use needs to be evaluated once it is released to the public. 6  

This section of the paper can be generated by ChatGPT if all results are pasted as input; however, this section also needs manual editing because inaccuracies are common. By discussing their research with ChatGPT, researchers can also identify potential limitations, discuss the broader implications of their findings, and propose future research directions. Although ChatGPT can generate suggestions and facilitate the thought process, it is important for researchers to critically evaluate the information provided and ensure that the Discussion and Conclusion sections align with the specific research objectives and findings of their study. Ultimately, ChatGPT can serve as a supportive tool in developing a comprehensive and well-rounded discussion and conclusion for research papers.

As per the author's experience, although ChatGPT is capable of creating references for an article, most of them are incorrect. So, using ChatGPT for creating references is not recommended. However, ChatGPT can convert references into any journaling style if the references are entered into ChatGPT and it is asked to convert them into a specific style.

Lack of domain expertise: ChatGPT is a general-purpose language model trained on a diverse range of Internet text, which means it may lack the specific domain expertise required for certain research topics. It may generate responses that are not accurate or well informed in specialized fields, potentially leading to incorrect or misleading information in research papers.

Inconsistency and variability: ChatGPT’s responses can be inconsistent and vary depending on the input phrasing or prompt formulation. This can lead to unpredictability in generating reliable and coherent content, requiring additional effort to refine and ensure accuracy in research papers.

Limited control over output: Although researchers can guide the model’s responses through prompts, ChatGPT’s generation process is still primarily autonomous. Researchers have limited control over the precise content and structure of the generated text, which may require careful editing and review to align with specific research goals, standards, and above all, accuracy.

Biases and ethical considerations: Language models like ChatGPT can inadvertently reflect biases present in the training data. These biases may perpetuate existing societal or cultural biases in research papers, potentially leading to unfair or discriminatory content. The careful examination and mitigation of biases are crucial to ensure ethical and unbiased research output. 7  

Lack of interpretability: ChatGPT’s decision-making process is complex and not easily interpretable. Researchers may struggle to understand the reasoning behind the model’s generated responses, making it challenging to assess the reliability and credibility of the information provided. Ensuring transparency and interpretability in research papers becomes more challenging with such models. ChatGPT should cite the sources for its data, like Google Bard does.

Plagiarism concerns: Because of its vast training data from the Internet, ChatGPT may inadvertently generate text that resembles or replicates existing content without proper citation or attribution. Researchers must be cautious about unintentional plagiarism and ensure that generated content is appropriately referenced and original. So, all ChatGPt-generated articles need to be double checked using antiplagiarism software.

In this commentary I have provided a comprehensive step-by-step guide for researchers and authors on harnessing the power of ChatGPT in the realm of research and publication. By exploring crucial aspects, such as data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations, the guide equips researchers with the necessary knowledge and tools to effectively integrate ChatGPT into their scientific workflows. 8  

Through clear instructions, examples, and guidelines, researchers can navigate the complexities of using ChatGPT, leading to enhanced productivity and improved quality in their research output. Moreover, I address the challenges associated with biases, interpretability, and plagiarism concerns, ensuring the responsible and ethical usage of ChatGPT as a research tool.

The significance of this research lies in its ability to bridge the gap between the rapid advancements in language models like ChatGPT and the research and publication process. By empowering researchers with the skills to leverage ChatGPT effectively, this guide fosters innovation, drives scientific progress, and opens up new possibilities for transformative contributions to various fields. 9  

As language-driven technologies continue to evolve, researchers must stay abreast of the latest advancements and best practices. The step-by-step guide presented in this commentary serves as a valuable resource, providing researchers with the knowledge and guidance necessary to maximize the potential of ChatGPT in their research endeavors. By embracing the capabilities of ChatGPT and ensuring its responsible and ethical use, researchers can revolutionize the way research and publications are conducted. With ChatGPT as a powerful tool in their arsenal, researchers are poised to make significant strides in their respective fields, pushing the boundaries of scientific knowledge and ushering in a new era of language-driven innovation. 10  

However, and to reiterate, I cannot overemphasize that ChatGPT has, at present, many disadvantages, including inconsistencies, bias, and plagiarism concerns, that must be addressed by the human author before the article is submitted for publication to a journal, as well as prior to publication, because the human author(s) is solely responsible for their research integrity and accurate reporting.

In conclusion, I have attempted to provide researchers with a comprehensive understanding of how to effectively leverage ChatGPT for research and publication purposes. It has also highlighted the problems and precautions that the human author(s) must take before publishing ChatGPT-generated content. By embracing this step-by-step guide, researchers can unlock the full potential of ChatGPT, driving scientific progress and shaping the future of research and publications.

Please use ChatGPT only if allowed by your institution, research lab, and the journal in question.

Please acknowledge ChatGPT within your manuscript/published paper wherever you are using it.

Please do not fabricate or plagiarize data. ChatGPT can be used only for summarizing texts, improving English writeups, and brainstorming ideas, and not for creating fabricated research raw data.

The author acknowledges that this article was partially generated by ChatGPT (powered by OpenAI’s language model, GPT-3; http://openai.com ). The editing was performed by the human author.

Disclosure. The author declare no conflicts or financial interest in any product or service mentioned in the manuscript, including grants, equipment, medications, employment, gifts, and honoraria.

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• Published: 28 July 2023

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Application ChatGPT in conducting systematic reviews and meta-analyses

• Simpy Amit Mahuli 1 ,
• Arpita Rai 2 ,
• Amit Vasant Mahuli 3 &
• Ansul Kumar 4  

British Dental Journal volume  235 ,  pages 90–92 ( 2023 ) Cite this article

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Systematic reviews and meta-analyses, which involve thorough literature searches and synthesis, are essential for evidence-based decision-making. With the growing number of publications, thorough review takes more time. A systematic review often takes more than 15 months to complete, and the long conception-completion interval may render a systematic review outdated by the time they are ready to be submitted and published. 1 , 2

Artificial intelligence (AI)-based quick approaches are being developed in response to the growing demand for screening and data extraction techniques that are more effective. These techniques automate decision-making by utilising machine learning (ML) algorithms and natural language processing (NLP) to extract pertinent information from textual material. These AI-based methods have the potential to accelerate the processes of systematic reviews and evidence synthesis while requiring less human labour. 3 , 4

ChatGPT is a Large Language Model (LLM) developed by OpenAI (OpenAI, L.L.C., San Francisco, CA, USA) which has tremendous potential to revolutionise the healthcare industry. ChatGPT has been effectively used for a variety of tasks in healthcare, including conducting literature reviews, analysing datasets, writing academic papers, documentation, and enhancing clinical workflow. ChatGPT is a significant advancement in the field of NLP. It generates human-like text by mimicking human language processing abilities using deep learning techniques and neural networks. Owing to its training on diverse datasets, it is able to provide pertinent responses to human prompts by processing large amounts of information. The easy accessibility and free availability have contributed to the success ChatGPT version 3.5 platform. 5

We tried to use ChatGPT for conducting Risk of Bias analysis and data extraction from a randomised controlled trial. The response of ChatGPT was surprising, to say the least. Conducting such processes through ChatGPT is simple and straightforward.

Firstly, to conduct a ROB analysis effectively using AI, obtaining the full-text version of the article under evaluation is crucial. This ensures that all relevant information and details necessary for the assessment are available. As an AI tool, it does not have real-time browsing capabilities, so it cannot search the internet or access the latest research articles. Additionally, it being a text-based AI, we cannot upload or import text/pdf files into the chatbox. However, ChatGPT can still try to assist us with general questions or provide guidance based on the information we provide from the study. If we have any specific questions or excerpts from the study that we would like ChatGPT to analyse or discuss, we can paste them into the chat box, and ChatGPT will do its best to assist.

AI provides validation to the information obtained through human effort and may even catch some details that are missed by the human eye.

Secondly, we need to provide clear and specific instructions to the tool for it to provide an appropriate response. Hence when prompted 'Can you use the ROBINS-I tool to evaluate "(Materials and methods from the full-text article)"', it generated a detailed response highlighting the various lacunae in the methodology in context of the Biases included in the ROBINS-I tool ( Fig. 1 and Fig. 2 ). This assessment does not eliminate the need for a human expert; however, it considerably reduces the time and effort required for the process. Also, AI provides validation to the information obtained through human effort and may even catch some details that are missed by the human eye. Additionally, ChatGPT is extremely helpful in the interpretation of studies for those who are not so fluent in the language. While ChatGPT can comprehend and generate text in languages other than English to some extent, its proficiency may vary across different languages. It's worth noting that ChatGPT's performance is generally more robust in English, as the majority of its training data is in English.

Screenshot of query for RoB analyis

Screenshot of ChatGPT's response to RoB analysis

Next, we tried to use ChatGPT for data extraction. By sharing the complete text and specifying the desired information or data to be extracted, AI can be of assistance. Hence, following various prompts from us, ChatGPT extracted data like mean values, standard deviation and sample size for study groups and sub-groups and presented it. Also, it was able to extract information from the tables provided, though it is not possible to paste a table in the chatbox. We can paste the data in the table en masse into the chatbox and it was able to interpret and extract information from it ( Fig. 3 and Fig. 4 ). Needless to say, this will reduce the time required for data extraction as well as ensure accuracy of the values, thereby reducing human errors.

Screenshot of query for data extraction from text

Response from ChatGPT for various queries for data extraction

AI methods are increasingly integrated into healthcare reviews to streamline processes. A recent systematic review by Blaizot et al. identified and examined automated tools and platforms that utilise artificial intelligence (AI) techniques. It assessed the pros and cons associated with the use of these methods in conducting systematic reviews. They identified various tools like Rayyan, Robot Reviewer, EPPI-reviewer, SWIFT-review, and Abstrackr which were employed for different review stages. Most included reviews acknowledged that screening with AI methods generally demonstrates low risks and enhances efficiency. However, possibility of missing relevant articles and issues in data extraction required human intervention. 4

ChatGPT possesses several distinct advantages in comparison to other AI tools. Its ability to retain context and coherence during conversations equips it to comprehend and respond to complex queries. It is extremely versatile which is demonstrated through its proficiency in handling various tasks, including factual inquiries, explanatory responses, creative content generation, and problem-solving assistance. ChatGPT is continuously evolving through regular updates and fine-tuning based on user feedback and new training data, enhancing its performance and accuracy over time. 5

It is crucial to acknowledge that ChatGPT also has limitations. These include the potential for generating incorrect or biased responses and its reliance on pre-existing data. Users should exercise critical thinking and independently verify information obtained from any AI tool. Currently, it is unable to process visual information; however, this issue has been addressed in ChatGPT 4.0. Additionally, the model's output heavily relies on user input; minor changes in the query can lead to significant alterations in the response. 5

This was the first attempt to test the feasibility of using ChatGPT in the tedious task of conducting systematic reviews and meta-analyses. It shows promise in reducing workload and time, but careful implementation and validation are necessary. We as researchers need to interact more with this tool to completely understand its applicability in generating evidence.

Borah R, Brown A W, Capers P L, Kaiser K A. Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry. BMJ Open 2017; doi: 10.1136/bmjopen-2016-012545.

Yaffe J, Montgomery P, Hopewell S, Shepard L D. Empty reviews: a description and consideration of Cochrane systematic reviews with no included studies. PLoS One 2012; doi: doi: 10.1371/journal.pone.0036626.

Chollet F. Deep learning with Python. pp 361. Shelter Island, New York: Manning Publications Co, 2018.

Blaizot A, Veettil S K, Saidoung P, Moreno-Garcia C F et al . Using artificial intelligence methods for systematic review in health sciences: A systematic review. Res Synth Methods 2022; 13: 353-362.

OpenAI. Introducing ChatGPT. Available at: https://openai.com/blog/chatgpt (accessed 19 May 2023).

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PhD Scholar, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi – 834009, India

Simpy Amit Mahuli

Associate Professor, Oral Medicine and Radiology, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi – 834009, India

Associate Professor, Public Health Dentistry, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi – 834009, India

Amit Vasant Mahuli

Associate Professor, Cardiothoracic and Vascular Surgery, Dental College, Rajendra Institute of Medical Sciences, Bariatu, India

Ansul Kumar

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Correspondence to Simpy Amit Mahuli , Arpita Rai , Amit Vasant Mahuli or Ansul Kumar .

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Mahuli, S., Rai, A., Mahuli, A. et al. Application ChatGPT in conducting systematic reviews and meta-analyses. Br Dent J 235 , 90–92 (2023). https://doi.org/10.1038/s41415-023-6132-y

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How to Use ChatGPT to Write a Literature Review With Prompts

Are you struggling with writing a literature review for your research paper?

Do you find it challenging to organize your thoughts and present a cohesive and engaging review?

Look no further, as this step-by-step guide will walk you through how to use ChatGPT to write a literature review effortlessly and effectively.

With the assistance of ChatGPT, you can enhance your writing process and create a well-structured literature review that will impress your readers and save your time in research.

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Table of Contents

Step 1: Familiarize Yourself with ChatGPT

To get started, visit the official website of ChatGPT at chat.openai.com

Take a moment to explore the features and functionalities offered by this powerful writing assistant.

You’ll find a user-friendly interface that allows you to interact with the model and generate high-quality content effortlessly.

Step 2: Understanding Prompts

Prompts act as a guiding framework for ChatGPT , providing it with the necessary context to generate accurate and relevant content.

When writing a literature review, you can leverage prompts to direct the AI’s attention towards specific areas or topics you want to cover.

This ensures that the generated text aligns with your intended purpose.

Step 3: Crafting an Effective Prompt

To write a compelling literature review, it’s crucial to formulate an effective prompt.

A well-crafted prompt should be clear, concise, and include specific instructions to guide the AI model.

Craft a prompt according to the requirements of your study. Provide detailed information about what you want to be included in your literature review. You need to give detailed information about the variables that you have used in the study, the relationships between them, and the research hypothesis .

Example: Prompt # 1

Let’s consider an example of a prompt for a literature review on “The Impact of Artificial Intelligence in Healthcare”:

Example: Prompt # 2

Write a literature review of a research paper. Topic: Effects on Stress on digital hoarding behavior of an Employee. The mediating role of procrastination and moderating role of work overload. Variab les: Stress, digital hoarding, procrastination, and work overload. Independent Variable: Stress, Dependent Variable: digital hoarding, Mediator: procrastination, Moderator: work overload. Provide separate definition of each variable. After that explain the relationships between variables. Research Hypothesis: There are 3 hypotheses. H1: Stress has positive influence on digital hoarding. H2: Procrastination is mediating the relationship of stress and digital hording. H3 : Workload moderates the relationship positively of stress and procrastination in an employee. Time_Period: 2015-2023 Include the authors and references in the literature review. Also Include citations. The references should be provided at the end.

By providing a detailed prompt like the one above, you ensure that ChatGPT understands the specific requirements of your literature review, enabling it to generate relevant and insightful content.

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Step 4: Interacting with ChatGPT

Once you have a well-crafted prompt, it’s time to interact with ChatGPT and generate your literature review.

On the website, you’ll find a text input field where you can enter your prompt. Simply copy and paste the prompt we discussed in the previous step into the input field and press the “Generate” button.

ChatGPT will then process the prompt and generate a response in real-time. The generated content will be based on the data it has been trained on and the context provided by the prompt.

Output provided by the ChatGPT

Literature Review

Title: Effects of Stress on Digital Hoarding Behavior of an Employee: The Mediating Role of Procrastination and Moderating Role of Work Overload

Introduction: The rapid advancement of technology and the increasing reliance on digital platforms have transformed the way individuals manage and organize their information. However, this digital age has also given rise to new behavioral patterns, such as digital hoarding, which refers to the excessive accumulation and difficulty in discarding digital files and data. Digital hoarding can have significant consequences for individuals, particularly in a work setting, where it can lead to decreased productivity, increased stress, and impaired decision-making. This literature review aims to explore the effects of stress on digital hoarding behavior among employees, while considering the mediating role of procrastination and the moderating role of work overload.

Definition of Variables:

• Stress: Stress is a psychological and physiological response to external pressures or demands, characterized by feelings of tension, anxiety, and unease. In the context of this research, stress refers to the emotional and cognitive strain experienced by employees in their work environment, which may arise from factors such as excessive workload, time pressure, or interpersonal conflicts.
• Digital Hoarding: Digital hoarding is a behavioral tendency characterized by the excessive accumulation and reluctance to delete or organize digital files, documents, emails, or other forms of electronic data. It represents a disorganized and cluttered digital environment, resulting in difficulties in locating and managing information effectively.
• Procrastination: Procrastination refers to the act of delaying or postponing tasks or activities that need to be accomplished. In the context of this research, procrastination is viewed as a mediator variable, playing a role in the relationship between stress and digital hoarding. It represents a cognitive and behavioral tendency to engage in non-essential activities or tasks that provide temporary relief from stress, leading to the neglect of important tasks, including digital file management.
• Work Overload: Work overload refers to a state in which an individual is faced with an excessive amount of work or tasks that exceed their available resources, including time and energy. As a moderating variable in this study, work overload is expected to influence the relationship between stress and procrastination. High levels of work overload may intensify the impact of stress on procrastination tendencies, exacerbating digital hoarding behavior.

Relationships between Variables: The proposed research hypotheses aim to investigate the relationships among the variables in the context of stress, digital hoarding, procrastination, and work overload.

Hypothesis 1 (H1): Stress has a positive influence on digital hoarding. This hypothesis suggests that higher levels of stress experienced by employees will be associated with increased digital hoarding behavior. Previous studies (Smith et al., 2017; Johnson & Brown, 2019) have indicated a positive relationship between stress and hoarding tendencies, suggesting that individuals may resort to hoarding behaviors as a coping mechanism to manage stress.

Hypothesis 2 (H2): Procrastination mediates the relationship between stress and digital hoarding. This hypothesis posits that procrastination acts as a mediator, partially explaining the relationship between stress and digital hoarding behavior. Research by Roberts and Zomer (2016) has highlighted the role of procrastination in information overload and disorganization, which aligns with the concept of digital hoarding.

Hypothesis 3 (H3): Work overload moderates the relationship between stress and procrastination. This hypothesis suggests that work overload enhances the positive relationship between stress and procrastination. The presence of high workloads can intensify the impact of stress on procrastination tendencies, leading to greater digital hoarding behavior. This is supported by studies conducted by Miller and Brown (2018) and Thompson et al. (2021), which have demonstrated the influence of work overload on procrastination behavior.

Conclusion: This literature review has provided an overview of the effects of stress on digital hoarding behavior among employees, considering the mediating role of procrastination and the moderating role of work overload. The identified research hypotheses (H1, H2, H3) will serve as a foundation for further empirical investigation to deepen our understanding of the complex relationships between these variables. By examining the impact of stress, procrastination, and work overload on digital hoarding behavior, organizations can develop strategies to promote healthier digital practices and enhance employee productivity.

References: Johnson, A. M., & Brown, T. A. (2019). Examining the relationship between stress, anxiety, and hoarding: A systematic review and meta-analysis. Journal of Obsessive-Compulsive and Related Disorders, 23, 100468.

Miller, R. B., & Brown, T. A. (2018). The relationship between work overload and mental health symptoms in firefighters: The moderating role of perceived supervisor support. Journal of Workplace Behavioral Health, 33(3), 213-229.

Roberts, L. D., & Zomer, A. C. (2016). The procrastination–information systems quality link: The mediating role of self-efficacy. Computers in Human Behavior, 65, 167-176.

Smith, C. G., et al. (2017). The relationship between hoarding symptomatology, compulsive buying, and obsessive-compulsive disorder. International Journal of Cognitive Therapy, 10(4), 332-348.

Thompson, M. A., et al. (2021). Work overload and turnover intentions: The mediating role of procrastination and the moderating role of neuroticism. Journal of Vocational Behavior, 128, 103603.

Step 5: Refining and Polishing

After ChatGPT generates the initial response, it’s time to refine and polish the content. Review the output carefully, ensuring that it aligns with the objectives of your literature review.

You can ask ChatGPT to provide much more detailed explanation on the variable which evr you would like.

Its good to provide ChatGPT detailed prompt to get better results. If you provide much detailed prompt, ChatGPT would write literature review according to your needs.

Note: The literature review that you would get is plagiarism-free. This is another benefit of using chatgpt to write literature review.

As an AI-powered writing assistant, ChatGPT provides a starting point for your literature review.

It can help you brainstorm ideas, explore different perspectives, and save time on the initial drafting process. However, it’s essential to remember that human judgment and expertise are still vital in crafting a comprehensive and well-rounded literature review.

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Step 6: Iterative Process

Writing a literature review is often an iterative process. You may need to go through multiple rounds of generating and refining the content until you achieve the desired outcome. Take advantage of ChatGPT’s capabilities to experiment with different prompts , explore diverse angles, and refine your review further.

By leveraging the power of ChatGPT and following this step-by-step guide , you can streamline your literature review writing process and enhance the quality of your work.

ChatGPT is a valuable tool for writing literature reviews. By following the steps outlined in this guide , you can effectively utilize ChatGPT to generate high-quality content for your literature review.

Remember, though, that while ChatGPT is a powerful AI model, it’s essential to review and refine the generated content to ensure it aligns with your specific requirements.

Other articles

Please read through some of our other articles with examples and explanations if you’d like to learn more.

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Literature Reviews

• Getting Started
• Choosing a Type of Review
• Developing a Research Question
• Searching the Literature
• Searching Tips
• ChatGPT [beta]
• ChatGPT Resources
• Documenting your Search
• Using Citation Managers
• Concept Mapping
• Writing the Review
• Further Resources

UM's Report on GenerativeAI

The initial report from the U-M Generative Artificial Intelligence Advisory (GAIA) Committee.

—User-friendly Interface that allows faculty, staff and students to engage in chat-based queries and benefit from the expertise of GENAI technology

— U-M GPT, enhances, teaching learning research in collaboration, providing a valuable and equitable resource for the entire university community

— designed to be accessible, including for use with screen readers

— provides access to GPT-3.5 and GPT-4 with no charge

https://chat.openai.com

• The knowledge cutoff for the ChatGPT 3.5 is September 2021 and it has no access to the Internet. Academic users may consider alternatives such as  Semantic Scholar,  Elicit,  Consensus  or other AI-powered tools for doing  real-time  literature reviews.
• Input/ Output length  - ChatGPT-3.5 allows a maximum token limit of 4096 tokens. According to ChatGPT " On average, a token in English is roughly equivalent to 4 bytes or characters. English words are typically around 5 characters long. This means that, very roughly, you could fit around 800 to 1000 English words within 4096 tokens." 
• Notes : (1) According to ChatGPT, the generated responses are non-deterministic by default. So if you run the searches again and get slightly or very different results than the ones listed on this guide, it's likely due to this factor. (2) While ChatGPT or Bing Chat searches offer conversational interaction, they might not be a substitute for the rigor and reliability of traditional academic database searches.  

KEYWORD GENERATION

Write a literature review abstract based on the following keywords: Keywords: Artificial Intelligence, Employment Trends, Skill Development, Future Workforce

Infant death Neonatal mortality  (referring specifically to deaths within the first 28 days of life) Perinatal mortality  (referring to deaths occurring during the period from 22 completed weeks of gestation to 7 completed days after birth) Early childhood mortality  (referring to deaths occurring within the first five years of life) Child mortality  (referring to deaths occurring before the age of 18) [Press the  Regenerate  button to get more.]

• Example -   RELATED WORDS What are the related words of infant mortality?

Neonatal mortality, Post-neonatal mortality, Stillbirths, Low birth weight, Malnutrition, Infectious diseases, Vaccination, Maternal health,  Access to healthcare, Poverty, Social inequality, Sanitation, Hygiene, Water quality, Childbirth complications, Congenital abnormalities, Birth defects, Maternal age, Under-five mortality, Child mortality, Perinatal mortality, Preterm birth, Low birth weight, Sudden infant death syndrome (SIDS), Maternal mortality, Postnatal care, Malnutrition, Immunization, Access to healthcare, Clean water and sanitation, Congenital anomalies, Infant health disparities, Infant mortality rate (IMR), Infant survival.  

(("Infant Death"[Mesh] OR "Sudden Infant Death Syndrome"[Mesh] OR "Infant Mortality"[Mesh] OR "Perinatal Mortality"[Mesh] OR "Neonatal Mortality"[Mesh] OR "Fetal Mortality"[Mesh] OR "Infant Death" OR "Sudden Infant Death Syndrome" OR "Infant Mortality" OR "Perinatal Mortality" OR "Neonatal Mortality" OR "Fetal Mortality") AND ("Risk Factors"[Mesh] OR "Etiology"[Mesh] OR "Prevention and Control"[Mesh] OR "Interventions"[Mesh] OR "Public Health"[Mesh] OR "Health Disparities"[Mesh] OR "Healthcare Disparities"[Mesh] OR "Poverty"[Mesh] OR "Malnutrition"[Mesh] OR "Infection"[Mesh] OR "Congenital Abnormalities"[Mesh] OR "Prematurity"[Mesh] OR "Low Birth Weight"[Mesh] OR "Maternal Education"[Mesh] OR "Maternal Health"[Mesh] OR "Risk Factors" OR "Etiology" OR "Prevention and Control" OR "Interventions" OR "Public Health" OR "Health Disparities" OR "Healthcare Disparities" OR "Poverty" OR "Malnutrition" OR "Infection" OR "Congenital Abnormalities" OR "Prematurity" OR "Low Birth Weight" OR "Maternal Education" OR "Maternal Health"))

Comments and Suggestions: #1 -This search string may not work on all database platforms. For example,  Medline (OVID)  may not be able to run it,  Medline  &  CINAHL (EBSCO)  can run it without any problems while   PubMed  will run it but it will indicate which MeSH terms are not indexed. See PubMed's search  History and Details  under  Advanced . #2 -This is just one possible search string and you may need to adjust it based on your specific research questions and the databases you are using. #3 - It might be easier if you break the task into 3 parts: ask the chatbot give you the synonyms > ask it to give you the thesauri terms > and ask it to combine them.

RESEARCH QUESTION

Increased risk of sudden infant death syndrome (SIDS) Increased risk of premature birth Increased risk of low birth weight Increased risk of respiratory problems in newborns Increased risk of respiratory problems in infants exposed to secondhand smoke Increased risk of developing asthma and other respiratory illnesses later in life for infants exposed to secondhand smoke Please generate a literature review that addresses the research question: 'What are the effects of social media on the mental health of adolescents? [Author's note : If you ask for the specific studies, ChatGPT may generate   non-existent references or false knowledge. To find out   why Large Language Models   hallucinate, check out this WiKi article:  Hallucination (artificial intelligence)   and this blog post -   A Gentle Introduction to Hallucinations in Large Language Models  by Adrian Tam ]

DATABASE RECOMMENDATIONS  

Heath Science  -  Which databases to use to find articles on the EFFECTS OF MATERNAL SMOKING ON INFANT DEATH? PubMed:  This is a database of biomedical literature from the National Library of Medicine. It includes articles from medical journals and other sources on a wide range of health-related topics. Embase:  This is a database of biomedical literature that covers more international and pharmaceutical content than PubMed. It includes articles from medical journals and other sources on a wide range of health-related topics. Cochrane Library : This is a collection of databases that provides systematic reviews and meta-analyses of healthcare interventions, including interventions related to maternal smoking and infant death. Scopus:  This is a multidisciplinary database that covers research from a wide range of fields, including health sciences. It includes articles from scientific journals, books, and conference proceedings. Web of Science:  This is a database that covers research from a wide range of fields, including health sciences. It includes articles from scientific journals, books, and conference proceedings. CINAHL:  This is a database of nursing and allied health literature, including articles on maternal smoking and infant death. [Note: The response above was copied and pasted directly from ChatGPT. No editing was added.] Education  --  I am doing a  meta-analysis  on k-12 STEM education. What databases should I use? ERIC : This is a database of education research and information, including articles from journals, reports, and conference papers. It is a commonly used database for educational research. Education Source : This is a comprehensive database of education research and information, including articles from journals, books, and conference papers. Web of Science:  This is a multidisciplinary database that covers research from a wide range of fields, including education. It includes articles from scientific journals, books, and conference proceedings. Scopus:  This is another multidisciplinary database that covers research from a wide range of fields, including education. It includes articles from scientific journals, books, and conference proceedings. PsycINFO:  This is a database of psychology research, including articles from journals, books, and dissertations. It can be useful for research on STEM education that includes psychological factors. Cochrane Library : This is a collection of databases that provides systematic reviews and meta-analyses of healthcare interventions including interventions related to education.

Example:   ACT-AS-AN-EXPERT PROMPT Here's an alternative way to consolidate all the questions into a single consultation by using this popular Act-As-An-Expert prompt, aka, system message prompt:  I am going to conduct a systematic review on games and mathematics related to K-12 education  I want you to act as a systematic review expert. I will ask you some questions related to my research topic and you advise me on how to do it. 

GREY LITERATURE  

Please show me all the resources that offer grey literature for conducting research in the field of education     ERIC (Education Resources Information Center): https://eric.ed.gov/     OpenGrey: http://www.opengrey.eu/     British Education Index: https://www.ebscohost.com/academic/british-education-index     WorldCat: https://www.worldcat.org/     ProQuest Dissertations & Theses Global: https://www.proquest.com/products-services/pqdtglobal.html     EThOS (Electronic Theses Online Service): https://ethos.bl.uk/     Institutional Repositories of universities and academic institutions (search for specific institution repositories)     American Educational Research Association (AERA): https://www.aera.net/     National Education Association (NEA): https://www.nea.org/     Association for Supervision and Curriculum Development (ASCD): http://www.ascd.org/     RAND Corporation: https://www.rand.org/     National Center for Education Research (NCER): https://ies.ed.gov/ncer/     National Center for Education Statistics (NCES): https://nces.ed.gov/     European Educational Research Association (EERA): https://www.eera-ecer.de/     UNESCO International Institute for Educational Planning (IIEP): http://www.iiep.unesco.org/     Organization for Economic Cooperation and Development (OECD): https://www.oecd.org/education/     Education Development Center (EDC): https://www.edc.org/     National Institute for Educational Policy Research (NIER) - Japan: https://www.nier.go.jp/     Australian Council for Educational Research (ACER): https://www.acer.org/     Canadian Education Association (CEA): https://www.cea-ace.ca/ My topic is about stem education. Which grey literature databases should I use?    STEM Education Research Centre (SERC) Grey Literature Database    National STEM Education Research Repository (NSERR)    National Science Digital Library (NSDL)    STEM Education Resource Center (SERC) GrayLit Network    STEM Education Grey Literature Library

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80+ ChatGPT Prompts for Literature Review

Conducting a literature review can often seem like a daunting task. It's an essential part of academic and research work, involving comprehensive and critical analysis of previously published research related to a specific topic. The goal is to gain a deep understanding of the state of knowledge on the topic, identify gaps, and provide a foundation for further research.

Traditionally, literature reviews have been manual, time-consuming processes. However, the advancement of technology, especially Artificial Intelligence (AI), is reshaping this landscape. One such development is ChatGPT, an AI developed by OpenAI. This tool can assist researchers in conducting more efficient and thorough literature reviews.

In this blog post, we will delve into the ways that ChatGPT, with its remarkable language understanding and generation capabilities, can be used to streamline your literature review process.

From explaining the basic capabilities of ChatGPT to providing essential prompts and tips to conduct a literature review, this post will serve as a comprehensive guide for those looking to leverage AI for academic research.

Stay tuned as we navigate this fascinating convergence of AI and research, and explore the potential of ChatGPT in making literature reviews more efficient and effective.

Table of Contents

The Power of AI in Literature Reviews

The role of Artificial Intelligence (AI) in academia and research is expanding rapidly. AI has emerged as a game-changing tool that can significantly enhance the process of conducting literature reviews.

The Benefits of AI in Conducting Literature Reviews

There are numerous advantages to using AI for literature reviews. Let's delve into these benefits:

Time Efficiency

AI can streamline the literature review process, significantly reducing the time taken. With AI, you can quickly scan vast amounts of literature, saving valuable time that can be used for analysis and synthesis.

Comprehensive Coverage

AI algorithms are capable of scanning and analyzing a far greater volume of literature than a human could reasonably manage. This ensures a comprehensive and exhaustive review of existing literature.

Consistency and Bias Reduction

AI maintains a level of consistency that is hard to achieve manually. It does not suffer from fatigue or bias, ensuring that all relevant literature is considered fairly.

The Role of ChatGPT in Literature Reviews

ChatGPT, developed by OpenAI, has proven to be a valuable tool for conducting literature reviews. It is a language model that can understand and generate human-like text, making it an excellent tool for understanding complex academic literature and providing summaries or insights.

Here are some example prompts that can be used to guide ChatGPT in assisting with literature reviews:

Example Prompts:

Generate a summary of this research paper.

What are the key findings of this study?

How does this research contribute to the field of [specific field]?

Identify the strengths and weaknesses of this study.

Compare this study with the previous study on the same topic.

What are the research gaps identified in this literature?

What future research directions are suggested by this study?

Preparing for a ChatGPT-Assisted Literature Review

Before diving into a literature review with ChatGPT, you need to set the stage right. Preparation is crucial to ensuring you get the most out of your AI-assisted literature review process.

Detailed Steps on How to Set Up for a Literature Review Using ChatGPT

• Understand Your Topic : Before starting, ensure you have a clear understanding of your topic and the specific aspects you want to focus on in the literature review.
• Gather Your Materials : Collect all the papers, articles, and sources you plan to include in your literature review.
• Organize Your Materials : Categorize your sources based on various parameters like theme, methodology, results, etc. This will make it easier to navigate through them during the review.
• Prepare Your Prompts : Create a list of prompts you plan to use with ChatGPT. These prompts should be designed to extract the information you need from each source.

Tips for Effective Use of ChatGPT in Literature Review

Preparing a list of keywords or topics.

Start with a broad overview of your research topic and gradually narrow down the scope by identifying specific sub-topics, methodologies, or research questions you want to explore. Use these as keywords for your prompts.

Having Clear Objectives for the Review

Before beginning your review, clearly outline what you hope to achieve. This could be understanding the current state of research, identifying gaps, comparing methodologies, etc.

Understanding the Limits of AI Assistance

While ChatGPT is a powerful tool, it's essential to remember it is a tool and not a replacement for human analysis. Use it to process and summarize information, but the interpretation and synthesis of this information should be done by you.

Provide an overview of the literature on [specific topic].

Summarize the methodologies used in the studies on [specific topic].

Identify common themes in the literature on [specific topic].

What are the disagreements in the literature about [specific topic]?

Analyze the impact of [specific study] on the broader field of [specific topic].

What are the emerging trends in the literature on [specific topic]?

What are the commonly cited sources in the literature on [specific topic]?

Essential ChatGPT Prompts for Literature Review

ChatGPT is a powerful tool for conducting literature reviews, and the key to using it effectively is crafting the right prompts. These prompts guide the AI in scanning, analyzing, and summarizing the literature based on your specific needs.

Need To Write A Thesis? ➡️ 87+ ChatGPT Prompts for Thesis Writing

Initial Exploration of a Topic

When you're just starting a literature review, you'll need prompts that help you gain a broad understanding of your research topic. These prompts can assist in grasping the general landscape of the literature.

Give a brief overview of research done on [topic].

What are the prominent theories or models in [topic]?

What are the key debates or controversies in [topic]?

Who are the key authors or researchers in [topic]?

What methodologies are commonly used in studies on [topic]?

Summarize the historical development of [topic] in academia.

What have been the significant shifts or changes in [topic] over time?

Deep Diving into Specific Studies

Once you have a broad understanding, you'll want to delve into specific studies or papers. These prompts help you extract detailed information from individual sources.

Summarize the main arguments and findings of [specific paper].

What methodology does [specific paper] use and why?

What are the strengths and weaknesses of [specific paper]?

How does [specific paper] contribute to the broader field of [topic]?

Compare the findings of [specific paper] with [another specific paper].

What future research does [specific paper] suggest or inspire?

How has [specific paper] been received or critiqued by other scholars in the field?

Comparing and Contrasting Different Works

ChatGPT can also help you identify similarities and differences between various sources. These prompts are useful for synthesizing information across multiple works.

Compare and contrast the methodologies of [paper 1] and [paper 2].

How do the findings of [paper 1] and [paper 2] agree or disagree?

How does [author 1]'s perspective on [topic] differ from [author 2]'s?

Compare the theoretical frameworks used in [paper 1] and [paper 2].

How does the approach to [topic] change over time as seen in [earlier paper] vs. [later paper]?

What themes are common across these studies on [topic]?

What disparities or contradictions exist in the literature on [topic]?

Summarizing Findings

Finally, as you conclude your literature review, you'll want to summarize your findings. These prompts help you consolidate your insights and present them clearly.

Summarize the key findings from my literature review on [topic].

What trends or patterns have emerged from the literature on [topic]?

What gaps or unanswered questions exist in the literature on [topic]?

How have perspectives on [topic] evolved over time, based on the literature?

What consensus, if any, exists in the literature on [topic]?

How does the literature inform our understanding of [topic]?

What future research directions are suggested by the literature on [topic]?

How to Create Effective ChatGPT Prompts

Crafting effective prompts for ChatGPT is part art, part science. It involves understanding the workings of the AI model, your research objectives, and the specific information you seek from your literature review.

Guidelines for Creating Effective ChatGPT Prompts

Here are some general guidelines to follow when crafting prompts for ChatGPT:

• Be Specific : The more specific your prompt, the more focused and relevant the AI's response will be.
• Use Clear Language : Make your prompts as clear and concise as possible. Avoid ambiguous terms and complex phrasing.
• Guide the AI : To get the best results, guide the AI towards the kind of response you're looking for. For example, if you want a summary, explicitly ask for a summary.
• Experiment and Iterate : Different prompts can yield different results. Don't be afraid to tweak your prompts and try different approaches to find what works best.

Tips for Refining and Iterating on Prompts

Prompts may not always work perfectly on the first try. Here are some tips for refining and iterating on your prompts:

• Analyze the Responses : Look at the AI's responses to understand how it is interpreting your prompts. If the responses are not what you expected, tweak your prompt to guide the AI more accurately.
• Try Different Angles : If a prompt isn't working, try approaching the question from a different angle or rephrasing the prompt.
• Split Complex Prompts : If a prompt is too complex, try splitting it into multiple simpler prompts.

Provide a summary of the main arguments in [specific paper].

What are the primary findings of [specific paper]?

Analyze the methodology used in [specific paper].

What are the implications of [specific paper] for future research?

Compare the findings of [specific paper] with those of [another specific paper].

What critiques have been made about [specific paper]?

What are the key themes across the literature on [specific topic]?

Examples of Good and Less Effective Prompts

Here are some examples of good and less effective prompts to help guide your prompt crafting:

Good Prompts:

Less Effective Prompts:

• Tell me about [specific paper]. (This is too vague and doesn't guide the AI towards the specific information you're seeking.)
• What's interesting about [specific paper]? (This prompt is subjective and may not yield useful information for a literature review.)
• What's everyone saying about [topic]? (This prompt is overly broad and might result in a wide range of responses that aren't focused enough for a literature review.)

Navigating Challenges in Using ChatGPT for Literature Reviews

While ChatGPT can be a powerful tool for conducting literature reviews, it's important to understand its limitations and potential challenges. Being aware of these can help you navigate the process more effectively.

Understanding the Limitations of ChatGPT

Despite its sophisticated capabilities, ChatGPT is not without its limitations. Here are some to keep in mind:

• Dependency on Input Quality : The quality of ChatGPT's responses depends on the quality and clarity of the prompts you provide.
• Lack of Critical Analysis : While ChatGPT can summarize and synthesize information, it can't provide the same level of critical analysis and judgment that a human researcher can.
• Potential for Misinterpretation : ChatGPT may occasionally misinterpret prompts or generate responses that miss the mark.

Overcoming Challenges in Using ChatGPT for Literature Reviews

Despite these limitations, there are ways to overcome the challenges in using ChatGPT for literature reviews:

• Carefully Craft Your Prompts : As noted earlier, the quality of your prompts greatly influences the AI's output. Spend time crafting and refining your prompts.
• Double-Check the Information : Always cross-check the AI's responses against the original sources to ensure accuracy.
• Combine AI and Human Analysis : Use ChatGPT as a tool to assist with your literature review, not as a replacement for your own analysis.

Here are some example prompts that can help you navigate potential challenges:

If the response seems off: Could you provide another summary of [specific paper]?

For double-checking information: What are the key findings of [specific paper]?

To ensure comprehensive coverage: Are there any other significant points in [specific paper] that haven't been mentioned?

If the response is too broad: Could you provide a more focused summary of the methodology in [specific paper]?

If the response is too narrow: What are the broader implications of [specific paper] for the field?

To clarify a complex point: Can you explain the main argument in [specific paper] in simpler terms?

To guide the AI's interpretation: Based on [specific paper], what are the potential areas for future research in this field?

More Great ChatGPT Prompts for Literature Reviews

An engaging literature review requires delving into a range of perspectives, methodologies, and findings within your chosen area of study. Crafting prompts that encourage varied and in-depth analysis can help you gain a comprehensive understanding of your topic. Here are more unique prompt ideas to enrich your literature review process using ChatGPT:

What are the key variables studied in relation to [topic]?

What theoretical frameworks have been applied to the study of [topic]?

Explain the significance of [specific study] in the field of [topic].

What are the ethical considerations discussed in the literature on [topic]?

How does [specific paper] challenge the prevailing understanding of [topic]?

What statistical methods are commonly used in studies on [topic]?

Discuss the influence of [specific author] on the research of [topic].

How have the research methods evolved over time in the study of [topic]?

What are the socio-cultural considerations in the literature on [topic]?

How does [specific paper] address the limitations of previous studies on [topic]?

Describe the study design of [specific paper] in the context of [topic].

What contributions does [specific paper] make to the existing literature on [topic]?

How have policy changes affected the research on [topic] over time?

What is the role of technology in the research of [topic]?

Identify the key longitudinal studies in the field of [topic].

What are the demographic considerations in studies on [topic]?

How does [specific paper] incorporate interdisciplinary approaches to [topic]?

What biases or assumptions are present in the literature on [topic]?

How does [specific paper] use empirical data to support its arguments on [topic]?

Discuss the replication studies in the field of [topic].

What are the implications of the literature on [topic] for practitioners?

How does the literature on [topic] align or contrast with public opinion?

What are the critical reviews or meta-analyses in the field of [topic]?

How does [specific paper] discuss the limitations of its own study on [topic]?

Identify the seminal works in the field of [topic] and explain their significance.

In the rapidly evolving world of AI, tools like ChatGPT have the potential to revolutionize the way we approach tasks such as literature reviews. This powerful AI model, when provided with carefully crafted prompts, can sift through and synthesize vast amounts of information, assisting you in navigating the complex landscape of academic literature.

Remember, the power of ChatGPT lies in its ability to respond to diverse prompts. While this blog post has offered several useful prompts and tips for conducting a literature review, don't hesitate to experiment and innovate with your own prompts. Your creativity and critical thinking, combined with ChatGPT's capabilities, can turn the daunting task of literature review into a more engaging and manageable process.

However, it's important to bear in mind the limitations of AI and to always complement AI-generated insights with your own critical analysis.

As you embark on your journey of exploration and discovery in your chosen field of study, may ChatGPT prove a valuable ally in helping you uncover the rich tapestry of ideas, debates, and breakthroughs that form the essence of academic literature.

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About R.J. Adams

R.J. is an artificial intelligence aficionado, committed to demystifying the intricacies of this cutting-edge technology for enthusiasts and novices alike. Leveraging his comprehensive background in internet marketing, online tools, and communications, he continually ventures into the landscape of newly released AI tools, conducting thorough tests and analyses, as well as finding the best prompts to use on the latest AI tools. He can also solve Rubik's Cube in under 2 minutes.

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This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.

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✨ NEW UPDATE: Literature Review Generator

A Custom GPT for Literature Review Generator has been released. It efficiently parses PDF files of research publications, extracts key themes, and creates a literature review section for your academic publications.

TRY NOW: https://chat.openai.com/g/g-G3U8pZGwC-literature-review-generator

ChatGPT Prompts for Academic Writing

In this repository, this list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans. Whether you're a student, researcher, or academic professional, these prompts can help you hone your writing abilities and tackle your writing projects with confidence.

Use directly in: chat.openai.com

The list is regularly updated, so you can keep track of new prompts by following this repository.

TIPS: As there is a limit to the number of words that can be used in ChatGPT, you can input your text multiple times using the prompt "Read this [PARAPGRAPH]:" and then run your final prompt "Considering the above text...".

You can also use prompts splitter: chatgpt-prompt-splitter.jjdiaz.dev

BRAINSTORMING

Article sections, title/topic sentence, introduction, literature review.

NOTE: Be careful and double-check article existence. ChatGPT may generate fake references

Methodology

Experiments, future works, improving language, summarization, plan/presentation, working with documents (available only in gpt-4).

Upload a PDF file of a paper then:

Upload a PDF file of your paper then:

Upload PDF files of papers then:

Upload a figure image then:

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Literature Review: Using ChatGPT

• About Literature Reviews
• How to Conduct your Lit Review
• A Few Writing Tips
• A Few Helpful Resources
• A Silly Example
• Using ChatGPT

What is AI, ChatGPT, and large-language modeling?

Artificial intelligence (AI) , in the context of this guide, is the use of datasets to train computer models to emulate human thought processes (IBM, n.d.). It is the emulation itself that may convince information consumers of the supposed "intelligence" of a machine; the more convincing the emulation, the more users are prone to trust the generated information.

ChatGPT is a generative large language model which has gained popularity since late 2021. The name stands for Chat Generative Pre-trained Transformer. GPT models are programmed to mimic the look and feel of engaging in a realistic conversation with another human being; however, bias and inaccuracy remain a considerable risk ( Kocoń, J., 2023).

Large language models (LLMs) are AI models that utilize networked datasets, emulating the neural pathways of the human brain, which assists in the appearance of actual cognition (Birhane et al., 2023).

Birhane, A., Kasirzadeh, A., Leslie, D., & Wachter, S. (2023). Science in the age of large language models. Nature Reviews Physics . https://www.nature.com/articles/s42254-023-00581-4

IBM. (n.d.). What is artificial intelligence (AI)? https://www.ibm.com/topics/artificial-intelligence Retrieved 27 April 2023.

Read more here: Generative AI in the Classroom & Research

What can I use ChatGPT for?

First and most importantly: check with your instructor that using generative AI is allowed for your class! This information should be added in your course syllabus with language indicating whether and to what extent AI can be used on assignments. If you are not sure, ask your instructor first .

From my biased perspective (that of a librarian), here is a brief list of ways you could use ChatGPT (if allowed for your class). This list is not exhaustive of all ideas.

• Keyword generation. Having trouble thinking of other ways to describe a concept? Ask ChatGPT to help!
• Narrowing/broadening your topic. Not getting any results? Getting way too many results? Use ChatGPT to help you brainstorm ways you can adjust your research question so that you can find the most effective sources.
• Setting the right tone. Want to create a patient education document in plain language but not quite sure how to translate the nursing jargon into easy-to-understand statements? ChatGPT can help you think of ways to ensure your tone matches your preferred audience.

What shouldn't I use ChatGPT for?

Because of bias and limitations from human contributions, it is imperative to approach generative AI with caution.

If your instructor has approved the use of ChatGPT or other generative AI in the class, below is a brief list of ways you should NOT use it. Again, this list is not exhaustive.

• Writing your assignments. This may be considered a form of plagiarism as the generated language is not your own original writing. If you use ChatGPT in this way without credit, you may be found in violation of the University's Academic Integrity policies. If you aren't sure, check with your instructor.
• Searching for sources. Do not use ChatGPT in lieu of conducting a literature search through the library resources. ChatGPT has a bad habit of "hallucinating" results; in other words, it will generate answers that sound right but that are not actual sources that exist. ChatGPT is not a search engine or a database.
• Creating accurate citations. ChatGPT is about as good as any other citation generator out there, which is to say that it is hit or miss. ChatGPT may leave off required elements of a citation, invent elements (for instance, generating incorrect DOIs or URLs), and fail to follow citation style formatting requirements. If you use ChatGPT for citation generation, be sure to double- and triple-check every citation thoroughly before submitting your assignment.

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Please follow the link below to complete a short survey and provide feedback on this guide.

Research Guide Satisfaction Survey

Should I cite ChatGPT?

Citing ChatGPT and other generative AI will allow your work to remain transparent while also demonstrating ethical considerations. If generative AI is used in research, best practice would dictate to mention the use of this tool in the narrative.

Suggestions for citations may be found below:

• American Psychological Association (APA)
• Chicago Manual of Style
• Modern Language Association (MLA)
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• Last Updated: Jan 12, 2024 1:21 PM
• URL: https://libguides.ecu.edu/lit_reviews

How to Use ChatGPT For Literature Review – Ultimate Guide

Writing literature review with ai.

Literature reviews are the bedrock of academic research, offering a comprehensive view of existing knowledge in a particular field.

The ability to harness the power of AI to assist in this crucial endeavor holds immense significance for scholars, saving time and effort while improving the quality and depth of their reviews.

The article is structured to walk you through the practical steps of using ChatGPT for literature reviews . We will start by understanding the fundamentals of literature reviews and tips and prompts for a more efficient research process.

Steps involved in writing a literature review

Traditional literature review writing often involves substantial time and effort, from searching for relevant papers and synthesizing information to ensuring proper citations. Literature review is conducted in following steps.

• Define your research question or topic
• Conduct a comprehensive literature search
• Review and select sources
• Summarize and categorize the literature
• Analyze and synthesize the literature
• Develop a structure for your literature review
• Write the literature review
• Revise and proofread
• Write a conclusion
• Citations and references

We will dive in how ChatGPT can helps us in each of these steps.

Step-by-Step Guide for Literature Review Writing with ChatGPT

Defining the scope and objectives.

ChatGPT can help you clarify and refine your research question or objective by engaging in a conversation to discuss your topic. It can suggest specific subtopics, keywords, or concepts that might be relevant to your literature review.

Engaging in a Conversation: Begin a conversation with ChatGPT to discuss your research on climate change. This can help you narrow down the scope of your review.

“I’m conducting a literature review on climate change. Can we discuss potential research questions and objectives to make it more specific?”

Suggesting Specific Subtopics: Ask ChatGPT for suggestions on subtopics related to climate change that you can include in your literature review.

“What are some specific subtopics or aspects of climate change that are currently of interest? I want to make sure my literature review covers key areas.”

Exploring Emerging Concepts: Engage with ChatGPT to explore emerging concepts or trends in climate change research that could be included in your objectives.

“Can you highlight any emerging concepts or areas of study within climate change that I should consider incorporating into my literature review?”

Refining Research Objectives: Use ChatGPT to refine your research objectives by asking for clarification or more specific details.

“My initial objective is to study the impact of climate change on agriculture. How can I make this objective more specific and focused?”

Alternative Perspectives: Request ChatGPT’s input on alternative perspectives or viewpoints within climate change research to broaden your scope.

“Are there alternative perspectives on climate change, perhaps from economic, social, or political viewpoints, that I should incorporate into my literature review?”

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Ethical Considerations For Using ChatGPT for Literature Review

AI tools like ChatGPT can be incredibly helpful, but they also come with ethical considerations. Researchers must ensure that the use of AI-generated content aligns with ethical standards. This involves:

• Authorship and Attribution: Clearly attribute AI-generated content to the tool used e.g., Generated with ChatGPT. Avoid presenting AI-generated content as if it were written by a human author.
• Plagiarism and Originality: Ensure that AI-generated content does not inadvertently lead to plagiarism. Verify the originality of the generated text and cite any sources or inspirations appropriately.
• Privacy and Data Security: Respect privacy concerns related to data used with AI tools. Protect sensitive information and follow data protection regulations when collecting or using data.

Best Practices for Using ChatGPT for Literature Review

Human researchers play a central role in the literature review process. AI can assist by accelerating content creation, but it can’t replace the depth of human expertise.

Researchers should leverage AI-generated content as a tool for enhancing their work, not as a substitute for their insights and judgment. Collaborative approaches, where humans work in tandem with AI, offer the best of both worlds.

You can Fine-Tune your ChatGPT experience by keeping following in mind.

• Edit and Refine: Review AI-generated content for clarity, accuracy, and relevance. Edit and rephrase text to align with the overall review’s tone and style.
• Provide Context: Add contextual information or expert insights that AI may not capture.
• Create a Well-Structured Prompt: Craft a detailed and specific prompt for ChatGPT. Clearly communicate the topic, subtopics, and context of your literature review. The more context you give it the better the output. So don’t hesitate and play while formulating your prompts.
• Fine-Tuning: If you are using ChatGPT – 4, then you can fine-tune the AI model. This involves training the model on specific datasets to align it with your research area, improving the quality of generated content.
• Review and Feedback: Regularly review the output and provide feedback to the AI model. This iterative process can help improve the accuracy and relevance of generated content over time.
• Interact with ChatGPT: Engage in a conversational dialogue with ChatGPT. Start with broad questions to gather initial insights and gradually delve into specific areas of interest. Be prepared to ask follow-up questions for deeper analysis.

Related: Best AI Tools For Writing Literature Review

Joe Daniels

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Using ChatGPT to conduct a literature review

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• 1 Department of Humanities, Czech University of Life Sciences Prague; Prague, Czech Republic.
• PMID: 36879536
• DOI: 10.1080/08989621.2023.2185514

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The role of ChatGPT in scientific communication: writing better scientific review articles

Jingshan huang.

1 School of Computing and College of Medicine, University of South Alabama, Mobile, AL, USA

2 Institute of Biochemistry and Molecular Biology, Institute of Biomedical Sciences, and Research Center for Cancer Biology, China Medical University, Taichung, Taiwan

Artificial intelligence tools represent an exciting opportunity for scientists to streamline their research and write impactful articles. Using artificial intelligence tools like ChatGPT can greatly improve writing review articles for scientists, by enhancing efficiency and quality. ChatGPT speeds up writing, develops outlines, adds details, and helps improve writing style. However, ChatGPT’s limitations must be kept in mind, and generated text must be reviewed and edited to avoid plagiarism and fabrication. Despite these limitations, ChatGPT is a powerful tool that allows scientists to focus on analyzing and interpreting literature reviews. Embracing these tools can help scientists produce meaningful research in a more efficient and effective manner, however caution must be taken and unchecked use of ChatGPT in writing should be avoided.

Introduction

The use of artificial intelligence (AI) tools such as ChatGPT (OpenAI, San Francisco, CA), is becoming increasingly important in scientific writing [ 1 - 5 ]. Whether you like or hate it, you need to face the fact that many other people are using ChatGPT to generate a lot of manuscripts right now [ 6 - 9 ]. Instead of resisting it or wasting your time to blame it, a better choice is for you to manage to use this powerful tool as your personal assistant, ethically, to increase your productivity and the quality of your works.

Using ChatGPT is a powerful tool to help scientists to write review articles more efficiently. Here are several reasons why you should use it to increase your proficiency in review writing, speed up your writing process, and save time [ 10 - 12 ].

It saves us time. Writing a review article can be a time-consuming process, involving extensive research, organization, and writing. AI tools like ChatGPT can speed up the writing process by automatically generating contents that can be further edited and refined by human authors, saving valuable time and resources.

It can help us to manage your data. Scientists often need to sift through large volumes of data and research papers to find relevant information for their review articles. AI tools like ChatGPT can assist with data management by analyzing and summarizing large amounts of information effectively and much more quickly than humans.

It can help us to improve the quality of our scientific writing. AI tools like ChatGPT can help to improve the quality of our writing by identifying potential errors, inconsistencies, or gaps in the argument. This can help human authors to refine their writing and ensure that their manuscript is accurate, well-structured, and well-supported by all available evidence as much as possible.

It can help us to keep a more balanced perspective. ChatGPT is not personally biased and can thus provide diverse perspectives on a given topic. This can be particularly useful in fields where there are many conflicting opinions and viewpoints, for example, promoting a ketogenetic diet for patients with the cardiovascular disease.

Moreover, if you are not a native English speaker, ChatGPT can be tremendously helpful. Are you tired of being criticized by the reviewers and editors on your English writings for not using the standard English, and suggest you to ask a native English speaker to help proofreading or even use the service from a professional English editor? ChatGPT can readily help you with grammar and sentence structure, suggest appropriate vocabulary choices, assist in translating text from one language to another, so on and so forth.

In addition to the above reasons, ChatGPT can help suggesting the article title, shortening, or expanding the abstract, discussing the results, and even recommending creative ideas.

ChatGPT can also help us to do the plagiarism detection. AI tools have been utilized to assist with detecting plagiarism by checking the similarity of the text with existing, published sources, helping to ensure that the manuscript is original and not copied from others’ work.

Overall, the use of AI tools like ChatGPT can significantly help scientists to write review articles more efficiently and accurately, thus improving the quality and impact of their research outcomes.

How ChatGPT works

ChatGPT is an AI language model developed by OpenAI [ 1 , 2 ]. It is based on a deep neural network architecture called the transformer model, which adopts the mechanism of self-attention, differentially weighting the significance of each part of the input data. The transformer model is pretrained on an extremely large corpus of text data to learn context and thus meaning by tracking relationships in sequential data such as the words in a sentence. After the pretrained phase, the transformer model is then able to generate natural language responses to user inputs.

When a user inputs a text prompt, ChatGPT generates a response based on its understanding of the input and the patterns it has previously learned from the text data it has been trained on. ChatGPT is capable of generating responses in a variety of formats, including short answers, long-form essays, and even conversation-style interactions [ 1 , 2 ].

ChatGPT works by breaking down the input text into a sequence of tokens, which are then processed by the transformer model to generate a probability distribution over the next token in the sequence. The model then selects the token with the highest probability and generates the corresponding output text. This process is conducted iteratively, with the model generating a new token and output text at each step, until a stopping criterion is met [ 1 , 2 ].

AI tools like ChatGPT is capable of generating responses in a wide range of domains, including scientific writing, creative writing, and general conversation. Its ability to generate natural language responses that are coherent and contextually relevant has made it a popular tool for a wide range of applications, including automated content creation, language translation, and natural language processing, just to name a few [ 1 - 5 , 13 - 16 ].

How ChatGPT can assist scientists in writing

Chatgpt can assist scientists in conducting literature reviews.

Topic selection: ChatGPT can help scientists to select a suitable topic for their literature review by generating relevant keywords and suggesting related and meaningful research areas. For example, a biologist could input “What are the latest research areas in the field of molecular biology?” and ChatGPT could generate a list of relevant keywords and research areas, such as “CRISPR-Cas9 gene editing”, “single-cell sequencing”, and “epigenetics”.

Literature search: ChatGPT can assist scientists in conducting literature searches by generating relevant search queries and suggesting relevant databases and resources. For example, a biologist could input “What are the best databases to search for articles on CRISPR-Cas9 gene editing?” and ChatGPT could generate a list of relevant databases and search queries, such as “PubMed”, “CRISPR-Cas9 AND gene editing”, and “CRISPR-Cas9 AND therapeutic applications”.

Article selection: ChatGPT can help scientists to select relevant articles for their literature review by generating summaries and providing context for each article. For example, a biologist could input “Can you summarize the findings of the latest review article on single-cell sequencing in cancer research?” and ChatGPT could generate a summary of the article, highlighting its key findings and relevance to the topic at hand.

Citation and referencing: ChatGPT can assist scientists in accurately citing and referencing their sources by generating the appropriate citation format and suggesting related articles to cite. For example, a biologist could input “How do I cite a journal article using the APA citation style?” and ChatGPT could generate the appropriate citation format and provide examples of related articles to cite.

Overall, ChatGPT can assist scientists in conducting literature reviews by helping them to select relevant topics, conduct literature searches, select articles, and accurately cite and reference their sources. By automating many of the time-consuming and tedious tasks associated with literature reviews, ChatGPT can help scientists to conduct more comprehensive and efficient reviews, leading to higher quality review manuscripts, and, in a much more efficient manner.

ChatGPT can assist scientists in developing outlines

Inputting the topic: Scientists can input the topic of their review article, for example, “The role of epigenetics in cancer development and treatment”.

Generating subtopics: ChatGPT can generate a list of subtopics related to the main topic. For example, ChatGPT could suggest subtopics such as “Epigenetic modifications in cancer cells”, “Epigenetic therapy for cancer”, and “Epigenetic biomarkers for cancer diagnosis”.

Organizing subtopics: ChatGPT can help scientists to better organize the subtopics into a logical outline for their review article. For example, ChatGPT could suggest organizing the subtopics under main headings such as “Introduction”, “Epigenetic modifications in cancer”, “Epigenetic therapy for cancer”, and “Epigenetic biomarkers for cancer diagnosis”.

ChatGPT can assist scientists in adding details

ChatGPT can assist scientists in adding greater details to the outline by suggesting key points and relevant literature for each subtopic. For example, ChatGPT could suggest adding details such as “Recent studies have identified several key epigenetic modifications that play a critical role in cancer progression, including DNA methylation and histone modifications”, and “Several epigenetic therapies, such as DNA methyltransferase inhibitors and histone deacetylase inhibitors, have shown promise in preclinical and clinical studies for treating various types of cancer”.

ChatGPT can assist in improving writing style

Inputting the text: Scientists can input the text they have written for their review article, for example, the abstract or introduction.

Analyzing the text: ChatGPT can analyze the text and provide suggestions for improvements. For example, ChatGPT can identify and highlight grammatical errors, ambiguous sentence structures, or repetitive phrases.

Suggesting improvements: ChatGPT can suggest improvements to the text based on its analysis results. For example, ChatGPT could suggest rephrasing sentences to further improve clarity, using more precise scientific terminology, or avoiding unnecessary jargons.

Providing examples: ChatGPT can provide examples of well-written scientific articles or sentences that illustrate the suggested improvements. For example, ChatGPT could suggest examples of articles with clear and concise writing style, or provide sentences that use technical terms accurately and in context.

Incorporating feedback: Scientists can incorporate the suggestions and examples provided by ChatGPT into their writing. They can also review the suggested changes and make any necessary adjustments to ensure that the changes fit with their intended writing style and tone.

Overall, ChatGPT can assist scientists in improving their writing style by analyzing their text, providing suggestions for improvements, and offering examples of well-written scientific articles or sentences. By incorporating ChatGPT’s suggestions, scientists can further improve the clarity, precision, and effectiveness of their scientific writing, leading to higher quality review manuscripts, and, more efficiently.

ChatGPT can be helpful for non-native English speakers writing review articles

Grammar and sentence structure: ChatGPT can provide suggestions for correct grammar and sentence structure, which can be particularly helpful for non-native English speakers who may struggle with these aspects of writing in English. The model can suggest alternatives for sentence construction and can identify errors in syntax or grammar.

Vocabulary: ChatGPT can suggest appropriate vocabulary choices and can provide synonyms and alternatives for words, which can help non-native English speakers to find best words to express their ideas.

Translation: ChatGPT can also be trained on text in languages other than English, which can be helpful for non-native English speakers who are writing review articles in their native language. The model can assist in translating text from one language to another, providing suggestions for sentence structure and vocabulary in the target language.

However, while ChatGPT can be helpful for non-native English speakers in the abovementioned ways, it is important to notice that it is not meant to be a substitute for a thorough understanding of the literature and concepts in the field. Non-native English speakers should still review and critically evaluate the text generated by ChatGPT to ensure accuracy and coherence, and should seek feedback from peers or colleagues who are fluent in English to ensure that the manuscript is of high quality.

Potential drawbacks or limitations of using AI in scientific writing

While the use of AI tools like ChatGPT can offer many benefits to scientific writing, there are also some potential drawbacks or limitations to consider.

Lack of context: AI tools like ChatGPT may lack the ability to fully understand the context and nuances of scientific writing, which may result in suggestions that are not always most relevant or appropriate.

Inaccurate or biased information: AI tools may introduce Inaccurate or biased information based on the data they were trained on, leading to suggestions or recommendations that may be biased or even inaccurate in some way.

Over-reliance: Over-reliance on AI tools can lead to a reduction in creative and critical thinking and the ability to make independent judgments about the quality of writing.

Technical limitations: AI tools may not be able to understand complex scientific concepts, technical terminology, or nuances of scientific writing, which can limit the usefulness of these tools.

Cost: Some AI tools may require a non-trivial investment, including licensing fees and training costs, which may be a barrier for some researchers or institutions.

It is important to note that these potential drawbacks or limitations can be mitigated by using AI tools in conjunction with human expertise, creative and critical thinking, and judgement. In addition, researchers and institutions should consider the costs and benefits of using AI tools, and weigh the potential drawbacks against the potential benefits before deciding whether or not to adopt these tools in their scientific writing process.

The risk of plagiarism when use AI to write review articles

The risk of plagiarism.

The risk of plagiarism when using AI to write review articles is a potential concern that should be taken seriously. AI tools like ChatGPT can generate text that may resemble text from other sources, including published articles or online resources, and may thus produce text that could be flagged as plagiarism.

However, it is important to note that the use of AI tools does not inherently increase the risk of plagiarism. Rather, the risk of plagiarism depends on how the AI-generated text is used and attributed. To minimize the risk of plagiarism, scientists should follow the below suggested protocol.

Use AI tools as a supplement rather than a replacement: Scientists should use AI tools to assist in writing their review article, but should not rely solely on AI-generated text. It is important to review and edit the AI-generated text to ensure that it is accurate and appropriate for the context of the article.

Properly attribute sources: When using AI-generated text, scientists should properly attribute any sources used in the text. This includes properly citing any direct quotations or paraphrased information and avoiding copying and pasting large portions of text without attribution.

Check for plagiarism: Scientists should use plagiarism-detection software to check their writing for any potential instances of plagiarism, including any text generated by AI tools. This can help identify any potential issues before the manuscript is submitted for publication.

Overall, while the risk of plagiarism when using AI to write review articles is a potential concern, it can be minimized by using AI tools responsibly and in conjunction with best practices for proper citation and attribution of sources. The bottom line is, plagiarism does happen with or without using AI tools.

How to avoid the risk of plagiarism

Using AI tools like ChatGPT to write review articles can be very helpful in speeding up the writing process and generating ideas. However, as discussed in the previous section, it is important to avoid the risk of plagiarism when using AI-generated text. Below are some tips on how to avoid plagiarism when using ChatGPT.

Understand the source of the text: When using ChatGPT to generate text, it is important to understand the source of the text. ChatGPT uses a large dataset of text to generate new text, so there is a risk that the generated text may include content that has been previously published. It is important to carefully review the generated text to ensure that it is not simply a reworded version of previously published content.

Use multiple sources: To avoid plagiarism, it is important to use multiple sources when writing a review article. ChatGPT can be used to generate text based on one or more sources, but it is important to supplement the generated text with information from other sources. This will help to ensure that the review article is not simply a regurgitation of previously published content.

Cite sources properly: ChatGPT can generate citations and references based on the input text, however, based on our experience, ChatGPT may suggest wrong references or even cite article references that do not exist; therefore it is extremely important to review and edit the generated citations and references to ensure their accuracy and completeness.

Use plagiarism-detection software: Plagiarism-detection software can be used to identify instances of plagiarism in the review article. This can help to ensure that the review article is original and not simply a reworded version of previously published content.

Review and edit carefully: Finally, it is important to review and edit the review article carefully to ensure that it is original and does not include any instances of plagiarism. This includes reviewing the text generated by ChatGPT and editing it as necessary to ensure its originality and accuracy.

In summary, while AI tools like ChatGPT can be very helpful in writing review articles, it is important to be vigilant about the risk of plagiarism and take steps to avoid it. By understanding the source of the text, using multiple sources, citing sources properly, using plagiarism-detection software, and reviewing and editing carefully, scientists can ensure as much as possible that their review articles are original and accurate.

Use ChatGPT to write review article need human oversight

While AI tools like ChatGPT can be incredibly helpful in the scientific writing process, it is important to note that they are not perfect and may produce errors or inaccuracies. As such, human oversight is essential to ensure that the content generated by ChatGPT is accurate, appropriate, and meets the needs of the intended audience.

Here are a few reasons why human oversight is necessary when using ChatGPT to write review articles.

Contextual understanding: AI tools like ChatGPT lack the ability to understand the full context of the scientific writing process. While they can generate text that may be grammatically correct and relevant to the topic, they may not be able to understand the broader implications of the content or the needs of the intended audience. As such, human oversight is necessary to ensure that the generated text is appropriate for the intended purpose.

Checking for accuracy: AI tools can generate text that is not always accurate or appropriate. For example, they may include factual errors or make assumptions that are not supported by the available evidence. Human oversight is necessary to ensure that the content generated by ChatGPT is accurate and supported by the available evidence.

Editing and formatting: AI-generated text usually requires further editing and formatting to meet the specific requirements of the review article, such as ensuring proper citation and formatting of references. Human oversight is necessary to ensure that the final product meets the necessary requirements and standards.

In summary, while ChatGPT can be a powerful tool for scientific writing, it is important to remember that it is never going to be a replacement for human expertise. Human oversight is necessary to ensure that the content generated by ChatGPT is accurate, appropriate, and meets the needs of the intended audience.

Conclusion remarks

In conclusion, the use of AI tools such as ChatGPT can significantly enhance both the efficiency and the quality of writing review articles for scientists. ChatGPT can help to speed up the writing process, facilitate collaboration among authors, and assist in improving writing style. However, it is important to keep in mind the limitations of ChatGPT’s capabilities for writing review articles in any expertise area, and to ensure that the generated text is carefully reviewed and edited by human authors to avoid the risk of plagiarism.

Despite these limitations, ChatGPT remains a powerful tool for scientists seeking to write high-quality review articles. By carefully inputting the relevant keywords and data, scientists can generate comprehensive and insightful reviews that summarize the latest advances in their field. With the assistance of ChatGPT, scientists can focus on analyzing and interpreting the results of their literature reviews, rather than spending hours poring over the literature and drafting summaries by hand.

Overall, the use of AI tools such as ChatGPT represents an exciting opportunity for scientists to streamline their research process and produce high-quality, impactful review articles in a timely and highly effective manner. As the field of AI continues to evolve, it is likely that we will see even more advanced tools that are tailored specifically to the needs of scientists. Potential examples include Google Bard, Microsoft Bing, and Jasper Chat, just to name a few. By embracing these tools and incorporating them into their research workflows, scientists can stay at the forefront of their fields and produce research that has an even more meaningful impact on society.

Acknowledgements

This work was in part funded by China Medical University Ying-Tsai Scholar Fund CMU109-YT-04 (to MT). This manuscript was conceived by MT, written by JH and MT, and revised by JH and MT. This article was not funded or supported by OpenAI. While some of the text was initially written with the help from ChatGPT by OpenAI, the content generated by ChatGPT has been carefully modified and verified by the human authors.

Disclosure of conflict of interest

International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability

ARTIIS 2023: Advanced Research in Technologies, Information, Innovation and Sustainability pp 313–323 Cite as

Leveraging Large Language Models for Literature Review Tasks - A Case Study Using ChatGPT

• Robert Zimmermann   ORCID: orcid.org/0000-0003-1819-6542 8 ,
• Marina Staab   ORCID: orcid.org/0009-0004-3807-5734 8 ,
• Mehran Nasseri   ORCID: orcid.org/0000-0003-3562-2240 8 , 9 &
• Patrick Brandtner   ORCID: orcid.org/0000-0002-0011-3502 8 , 9  
• Conference paper
• First Online: 20 December 2023

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1935))

Literature reviews constitute an indispensable component of research endeavors; however, they often prove laborious and time-intensive. This study explores the potential of ChatGPT, a prominent large-scale language model, to facilitate the literature review process. By contrasting outcomes from a manual literature review with those achieved using ChatGPT, we ascertain the accuracy of ChatGPT's responses. Our findings indicate that ChatGPT aids researchers in swiftly perusing vast and heterogeneous collections of scientific publications, enabling them to extract pertinent information related to their research topic with an overall accuracy of 70%. Moreover, we demonstrate that ChatGPT offers a more economical and expeditious means of achieving this level of accuracy compared to human researchers. Nevertheless, we conclude that although ChatGPT exhibits promise in generating a rapid and cost-effective general overview of a subject, it presently falls short of generating a comprehensive literature overview requisite for scientific applications. Lastly, we propose avenues for future research to enhance the performance and utility of ChatGPT as a literature review assistant.

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vom Brocke, J., et al.: Reconstructing the giant: on the importance of rigour in documenting the literature search process. In: ECIS 2009 Proceedings (2009)

Google Scholar  

Jozefowicz, R., Vinyals, O., Schuster, M., Shazeer, N., Wu, Y.: Exploring the limits of language modeling. arXiv (2016)

Uszkoreit, J.: Transformer: A Novel Neural Network Architecture for Language Under-standing – Google AI Blog (2017). https://ai.googleblog.com/2017/08/transformer-novel-neural-network.html

Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners, 1–9 (2019)

Ouyang, L., et al.: Training language models to follow instructions with human feedback. Adv. Neural. Inf. Process. Syst. 35 , 27730–27744 (2022)

Zhang, S., et al.: OPT: open pre-trained transformer language models. arXiv

Chakrabarty, T., Padmakumar, V., He, H.: Help me write a poem: instruction tuning as a vehicle for collaborative poetry writing. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 6848–6863 (2022)

Weidinger, L., et al.: Ethical and social risks of harm from Language Models (2021)

Weidinger, L., et al.: Taxonomy of risks posed by language models. In: 2022 ACM Conference on Fairness, Accountability, and Transparency, New York, NY, USA, pp. 214–229. ACM (2022). https://doi.org/10.1145/3531146.3533088

OpenAI: Introducing ChatGPT (2023). https://openai.com/blog/chatgpt

Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 4171–4186 (2019). https://doi.org/10.18653/v1/N19-1423

Leippold, M.: Thus spoke GPT-3: interviewing a large-language model on climate finance. Financ. Res. Lett. 53 , 103617 (2023). https://doi.org/10.1016/j.frl.2022.103617

Article   Google Scholar  

Brown, T.B., et al.: Language Models are Few-Shot Learners (2020)

Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998–6008 (2017). https://doi.org/10.48550/arXiv.1706.03762

Liu, Y., et al.: RoBERTa: a robustly optimized BERT pretraining approach. arXiv (2019)

Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 2020 , 5485–5551 (2020). https://doi.org/10.5555/3455716.3455856

OpenAI: GPT-4 Technical Report (2023)

Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., Iwasawa, Y.: Large Language Models are Zero-Shot Reasoners (2022)

Snæbjarnarson, V., Einarsson, H.: Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic. Proceedings of the Workshop on Multilingual Information Access (MIA), vol. , 29–36 (2022). doi: https://doi.org/10.18653/v1/2022.mia-1.4

Gao, T., Xia, L.,Yu, D. (eds.): Fine-tuning pre-trained language model with multi-level adaptive learning rates for answer selection, vol. (2019)

DeRosa, D.M., Lepsinger, R.: Virtual Team Success: A Practical Guide for Working and Learning from Distance. Wiley (2010)

Hosseini-Asl, E., Asadi, S., Asemi, A., Lavangani, M.A.Z.: Neural text generation for idea generation: the case of brainstorming. Int. J. Hum.-Comput. Stud. 151 (2021)

Palomaki, J., Kytola, A., Vatanen, T.: Collaborative idea generation with a language model. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, vol. 1–12 (2021)

Valvoda, J., Fang, Y., Vandyke, D.: Prompting for a conversation: how to control a dialog model? In: Proceedings of the Second Workshop on When Creative AI Meets Conversational AI, pp. 1–8 (2022)

Zeng, Y., Nie, J.-Y.: Open-Domain Dialogue Generation Based on Pre-trained Language Models

Li, D., You, J., Funakoshi, K., Okumura, M.: A-TIP: attribute-aware text Infilling via Pre-trained language model. In: Proceedings of the 29th International Conference on Computational Linguistics, pp. 5857–5869 (2022)

Rahali, A., Akhloufi, M.A.: End-to-End transformer-based models in textual-based NLP. AI 4 , 54–110 (2023). https://doi.org/10.3390/ai4010004

Ziegler, D.M., et al.: Fine-tuning language models from human preferences (2020). https://doi.org/10.48550/arXiv.1909.08593

Jiang, X., Liang, Y., Chen, W., Duan, N.: XLM-K: improving cross-lingual language model pre-training with multilingual knowledge. AAAI 36 , 10840–10848 (2022). https://doi.org/10.1609/aaai.v36i10.21330

Dunn, A., et al.: Structured information extraction from complex scientific text with fine-tuned large language models (2022)

Wu, T., Shiri, F., Kang, J., Qi, G., Haffari, G., Li, Y.-F.: KC-GEE: knowledge-based conditioning for generative event extraction (2022)

Santosh, T.Y.S.S., Chakraborty, P., Dutta, S., Sanyal, D.K., Das, P.P.: Joint entity and relation extraction from scientific documents: role of linguistic information and entity types (2021). https://ceur-ws.org/Vol-3004/paper2.pdf

Singh, V.K., Singh, P., Karmakar, M., Leta, J., Mayr, P.: The journal coverage of Web of science, Scopus and dimensions: a comparative analysis. Scientometrics 126 , 5113–5142 (2021). https://doi.org/10.1007/s11192-021-03948-5

Haman, M., Školník, M.: Using ChatGPT to conduct a literature review. Accountab. Res. 1–3 (2023). https://doi.org/10.1080/08989621.2023.2185514

Temsah, O., et al.: Overview of early ChatGPT’s presence in medical literature: insights from a hybrid literature review by ChatGPT and human experts. Cureus 15 , e37281 (2023). https://doi.org/10.7759/cureus.37281

Rahman, M., Terano, H.J.R., Rahman, N., Salamzadeh, A., Rahaman, S.: ChatGPT and academic research: a review and recommendations based on practical examples. J. Educ. Mngt. Dev. Stud. 3 , 1–12 (2023). https://doi.org/10.52631/jemds.v3i1.175

Gupta, R., et al.: Expanding cosmetic plastic surgery research using ChatGPT. Aesthetic Surgery J. (2023). https://doi.org/10.1093/asj/sjad069

Ouyang, L., et al.: Training language models to follow instructions with human feedback

OpenAI: Best practices for prompt engineering with OpenAI API (2023). https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api

OpenAI: Models (2023). https://platform.openai.com/docs/models/overview

BigScience Workshop: BLOOM. Hugging Face (2022)

Touvron, H., et al.: LLaMA: Open and Efficient Foundation Language Models (2023)

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Acknowledgments

This research has been funded by both the Government of Upper Austria as part of the research grant Logistikum.Retail and by the Christian Doppler Gesellschaft as part of the Josef Ressel Centre PREVAIL.

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Zimmermann, R., Staab, M., Nasseri, M., Brandtner, P. (2024). Leveraging Large Language Models for Literature Review Tasks - A Case Study Using ChatGPT. In: Guarda, T., Portela, F., Diaz-Nafria, J.M. (eds) Advanced Research in Technologies, Information, Innovation and Sustainability. ARTIIS 2023. Communications in Computer and Information Science, vol 1935. Springer, Cham. https://doi.org/10.1007/978-3-031-48858-0_25

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Title: can chatgpt write a good boolean query for systematic review literature search.

Abstract: Systematic reviews are comprehensive reviews of the literature for a highly focused research question. These reviews are often treated as the highest form of evidence in evidence-based medicine, and are the key strategy to answer research questions in the medical field. To create a high-quality systematic review, complex Boolean queries are often constructed to retrieve studies for the review topic. However, it often takes a long time for systematic review researchers to construct a high quality systematic review Boolean query, and often the resulting queries are far from effective. Poor queries may lead to biased or invalid reviews, because they missed to retrieve key evidence, or to extensive increase in review costs, because they retrieved too many irrelevant studies. Recent advances in Transformer-based generative models have shown great potential to effectively follow instructions from users and generate answers based on the instructions being made. In this paper, we investigate the effectiveness of the latest of such models, ChatGPT, in generating effective Boolean queries for systematic review literature search. Through a number of extensive experiments on standard test collections for the task, we find that ChatGPT is capable of generating queries that lead to high search precision, although trading-off this for recall. Overall, our study demonstrates the potential of ChatGPT in generating effective Boolean queries for systematic review literature search. The ability of ChatGPT to follow complex instructions and generate queries with high precision makes it a valuable tool for researchers conducting systematic reviews, particularly for rapid reviews where time is a constraint and often trading-off higher precision for lower recall is acceptable.

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Managers take note: You might be wondering if it's okay to   use ChatGPT for writing performance reviews , and understandably so.

Organizations increasingly rely on AI tools like ChatGPT for various tasks, and exploring their application in crafting insightful and effective performance reviews   can   save you time in the evaluation process.

However,   ChatGPT really isn't the best option . Here's why.

ChatGPT and similar general large language models work by predicting words based on statistical patterns.

They   don't really   understand what they're writing; they just regurgitate phrases they've learned from the internet - which happens to be filled with biased content. It's like a fancy word generator but not exactly the "brightest" tool in the shed. And you'll want a better tool when it comes to something as crucial as writing performance reviews for your team. In fact,   you absolutely need it .

Data Privacy

Additionally, data privacy is super important in generative AI, especially with big models like ChatGPT.

Like I mentioned, these models generate text that mirrors the patterns and content they were trained on. However, this also raises big privacy worries. A key problem is the chance of revealing sensitive data from the training data, which could accidentally be revealed in the generated content.

Even when trying to anonymize the data, there's still a chance of re-identification, putting people's privacy at risk.

Protecting data privacy is essential to building trust with users and stakeholders and following  rules like GDPR and CCPA . Making data privacy a top priority means respecting people's rights and supporting the ethical and responsible progress of AI technologies.

Thankfully, there are other options out there. You just need to know what to look for and how to use them safely. We've covered all the   dos and don'ts of using generative AI for performance reviews   before, so it's worth checking that out. Your team deserves a more thoughtful approach to feedback than what ChatGPT can offer.

Start writing actionable feedback with Textio

After all, this isn’t about just any performance — it's about theirs.

If you're interested in using a   purpose-built tool   for writing actionable and effective performance reviews for your team, you can   try out our free trial for Textio Lift.

How-To Geek

Stop wasting time making excel formulas, use chatgpt instead.

Why bother with tedious formulas when ChatGPT can do the heavy lifting for you?

Quick Links

How to get a quick excel formula from chatgpt, chatgpt can troubleshoot and tweak your formulas, you still need to check the formulas manually, key takeaways.

• You can use ChatGPT to create Excel formulas even without prior knowledge of the tool.
• ChatGPT can help you fix errors and incorrectly configured formulas.
• ChatGPT can make mistakes, so verify formula results manually for accuracy.

In a fast-paced work environment, you need to maximize efficiency, and AI tools like ChatGPT can make short work of tedious tasks, such as creating Excel formulas. If you haven't yet tried ChatGPT for custom Excel formulas, you're missing out on a serious game changer.

The tips provided in this article aren't limited to Excel; they're also applicable to other spreadsheet tools, such as Google Sheets and Apple Numbers. Additionally, this guide focuses on the free version of ChatGPT based on the GPT 3.5 model. If you have access to GPT 4, you can use the Advanced Data Analysis tool to take screenshots and upload Excel files directly to GPT 4 for a more seamless experience.

If you dread the mere thought of opening Excel, let alone creating formulas, you've come to the right place. ChatGPT offers you an easy way to create Excel formulas with zero practical experience required.

All you have to do is give ChatGPT an explanation of what you want to do, and it'll give you a formula, along with detailed instructions on how to implement it. Just make sure to mention the range (columns and rows) that you want to apply the formula to, and it'll do the rest for you. In this example, I have an assortment of orders for various items with varying prices and profit margins.

My goal is to calculate the revenue and profit for each order. While the formula required to do this isn't complex, let's just assume that I knew nothing about Excel, and it was my first day on the job. I'd turn to ChatGPT and ask it for a formula:

After pasting the formula into the rows, dragging it down to automatically fill the data , and changing the format to USD , I was left with exactly what I was looking for.

This is just a basic example to show you how ChatGPT can determine what formulas you need based on what you'd like to do. Let's do something slightly more complicated by asking it to help us calculate the average profit margin and most profitable item.

After implementing the formula, I was once again left with exactly what I was looking for. I double-checked the numbers by calculating everything manually to confirm the formulas worked correctly.

If you're already an Excel aficionado and prefer making formulas yourself, you can ask ChatGPT to suggest the best function for your unique scenario. Let's say I wanted to import information about the revenue and profits from my orders sheet to a tax sheet. ChatGPT gave me four viable formulas that I could use, along with a brief explanation of how they work.

These are just a few basic examples demonstrating what you can do with ChatGPT and Excel. You can use your AI buddy to build upon formulas and organize your data in any way you can imagine. There's even a new experimental function for custom GPT prompts . The point is that you never have to think about which formula to use or even know how it works. Still, it helps to know a thing or two about Excel to get the most out of it. Check out our Excel for Beginners guide for a quick crash course.

If you've subscribed to Copilot Pro, you can add GPT-4 Turbo directly to Excel . This integration allows Copilot to analyze your data and suggest relevant formulas in addition to providing direct access to GPT.

You Can Create Formatting Rules With ChatGPT

Excel has a complex interface that makes it hard to navigate, especially for novices, and conditional formatting rules require you to poke around to figure them out. In the following example, I have a list of articles with columns that track whether they have been written and have photos.

I gave ChatGPT detailed instructions to help me color-code the table so that I could keep track of what articles were still in progress. Here's my prompt, followed by ChatGPT's response:

I went through the steps exactly how ChatGPT laid them out, and the results are perfect. Even if I had no prior knowledge of using Excel, I would be able to create the formatting rule to keep the project organized.

Don't worry if one of the formulas ChatGPT gave you isn't working as intended—it happens to me all the time. The fix can range from telling ChatGPT, "Hey, this doesn't work." to explaining the problem in detail until ChatGPT figures out the issue.

In the following example, I wanted to calculate the return on investment for my articles, but the first formula that ChatGPT gave me didn't take into account whether the article had been written yet, making the formula show that I lost $100 for the last two articles. I informed ChatGPT about the discrepancy, and it gave me a new and improved formula.

You can also use ChatGPT to identify what's causing an error. Let's say an event organizer was trying to calculate the total number of passengers from each city using a simple addition formula and encountered the #VALUE! error because they mixed text and numbers. After explaining the issue to ChatGPT, it immediately recognized the error and gave a fix accompanied by a simple explanation.

While ChatGPT is undoubtedly one of the "smartest" tools humans have ever created, it's not perfect. It might create a formula that doesn't work correctly, which isn't a problem when Excel spits out an error. However, in instances where a formula seemingly functions correctly but has omitted an important parameter, it can create a false sense of security.

This behavior can mislead you into thinking that the data shown is correct when it's actually being miscalculated. This is why you have to double- and triple-check that your formulas are correct by calculating a few random entries manually. Also, if you gave ChatGPT specific cell ranges and then made changes after inserting the formula, you must ensure that your changes didn't affect the formula.

ChatGPT is a real Excel pro, with the caveat that it can't actually see or understand your sheets, so you have to make sure the formulas work correctly. All you need is a basic understanding of how Excel works, and ChatGPT can create advanced formulas tailored to your unique scenario.

Craft LinkedIn Summary with ChatGPT: A Step-by-Step Guide

Use ChatGPT to efficiently write a LinkedIn summary by setting up an account, preparing your information, and customizing the output. This process saves time and enhances the quality of your professional online presence.

Adding a personal touch to the AI-generated content will make your profile stand out.

Streamline the creation of your professional online presence and automate your LinkedIn profile enhancement with Bardeen.

How to Use ChatGPT to Write Your LinkedIn Summary

Creating a captivating LinkedIn summary can significantly impact your professional online presence, setting the tone for your profile and providing a snapshot of your career achievements and aspirations. In the era of artificial intelligence, leveraging tools like ChatGPT, developed by OpenAI, can streamline the process of crafting a compelling summary. This guide walks you through the steps to effectively use ChatGPT for enhancing your LinkedIn profile.

While manually writing a LinkedIn summary allows for a personalized touch, automating this process can save time and enhance your profile's effectiveness. Bardeen , paired with OpenAI, offers innovative automations for generating engaging professional summaries. Learn more .

Understanding ChatGPT for LinkedIn Summary Creation

ChatGPT is an AI-driven chatbot that utilizes advanced machine learning algorithms, enabling it to understand context and generate relevant text based on user prompts. It's built on the GPT (Generative Pre-trained Transformer) series of language models, which have been trained on vast amounts of internet data. This foundation allows ChatGPT to produce text that mimics human writing styles, making it an excellent tool for drafting professional summaries.

Benefits of Using ChatGPT for Your LinkedIn Summary

Employing ChatGPT for writing your LinkedIn summary offers several advantages:

• Time Efficiency: ChatGPT can generate a polished summary faster than writing from scratch.
• Professional Quality: Leveraging its advanced language capabilities, ChatGPT ensures your summary is well-structured and engaging.
• Customization: You can provide specific inputs to tailor the summary to your career goals.

Step-by-Step Guide to Writing Your LinkedIn Summary with ChatGPT

Follow these steps to create a standout LinkedIn summary using ChatGPT:

Step 1: Setting Up an Account

Sign up for an account on the OpenAI website using an email address, Google account, or Microsoft account. The platform is free, but a premium version, ChatGPT Plus, offers additional benefits.

Step 2: Prepare Your Information

Copy sections of your resume or LinkedIn profile to provide ChatGPT with the necessary context. Use prompts like:

• "I want you to write a compelling LinkedIn summary based on my work experience section."

Step 3 (Optional): Inquire About Required Information

If you don't have a finalized resume or LinkedIn profile, ask ChatGPT what information it needs to create a personalized summary.

Step 4: Review and Personalize

Request multiple summary options from ChatGPT, review them, and combine elements you like. Then, personalize the summary by:

• Checking grammar and punctuation.
• Enhancing vocabulary for clarity.
• Improving sentence flow for readability.

Optimizing Your LinkedIn Profile with ChatGPT

After crafting your summary, consider using ChatGPT for other aspects of your LinkedIn profile, such as job descriptions, headlines, and even crafting personalized messages to connections. Remember, while ChatGPT can provide a solid foundation, adding your personal touch will make your profile truly stand out.

Discover how Bardeen can further automate your LinkedIn efforts, including ChatGPT automations with Bardeen , to ensure your profile is as effective as possible.

Utilizing AI tools like ChatGPT can significantly enhance your LinkedIn profile's effectiveness, making you more visible to potential employers and connections in your industry. By following these steps, you can create a compelling LinkedIn summary that showcases your professional identity and goals.

Automate Your LinkedIn Summary with Bardeen and OpenAI

While writing a LinkedIn summary manually allows for a personalized touch, automating this process can save time and enhance your profile's effectiveness. Bardeen , paired with OpenAI , offers innovative automations that generate engaging professional summaries. This not only streamlines content creation but ensures your profile stands out to potential employers and connections.

• Generate LinkedIn Profile Summary with OpenAI : This playbook automates the creation of a concise LinkedIn profile summary, utilizing the power of OpenAI to highlight your professional background and expertise efficiently.

Explore these automations to enhance your LinkedIn presence with minimal effort. Start by downloading the Bardeen app .

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How to Use ChatGPT to Write a Poetry Book

I n the world of AI, ChatGPT is rising fast to be one of the most well-known services. For a creative writer, it can be a great deal of help in multiple ways. From generating ideas for overcoming writer’s block to researching themes for your next story, ChatGPT is the perfect assistant.

But, can it help with the entire process of creating a poetry book? If you ask the right questions, there’s no reason why it can’t.

Below is a guide on how to use OpenAI’s ChatGPT to write a poetry book, from brainstorming to publication.

Brainstorm Ideas

The beginning of every poetry book needs one thing: poems. Many times, the poems can be based on one theme or showcase a storyline.

To write poetry, though, you have to be in the right emotional headspace for it. If you’re not, it can be a bit difficult to scribe lines.

ChatGPT can help with that. Brainstorming ideas can come in the nature of prompts, collaboration, and even sharing other poetry to inspire your thought process.

If you’re curious about what topic your poetry should focus on, ask ChatGPT for a list of themes and pick which ones resonate with you.

You may already know what theme you’re going for. If so, you can ask for prompts about that theme or have ChatGPT ask you questions to help refine your ideas. The questions should be thought-provoking to help you infuse as much emotion into your work as you can. Remember, AI can’t feel, so it’s up to you to make your readers feel your art.

If you really want to test your poetic abilities, ask the AI to suggest a new poetic approach with steps to help guide you. Even if it doesn’t make it to a final draft, it’s still a good exercise to enhance your writing abilities.

Help With Language and Style

There are so many creative ways that ChatGPT can be used . Helping to build poems with fluid language and style is one of them.

Having refined language and style in a poem helps to express your ideas and emotions to your readers. If it’s inconsistent and hard to understand, your readers won’t be able to keep up with the art you’re trying to create in your book.

Using poetic devices can help to make a good poem great. Ask ChatGPT for a poetic device that will fit within the poem structure you’re going for.

You can also ask ChatGPT for some good imagery words that align with the subject of your poem. For example, if you’re writing about the moon’s reflection on top of the water, but you’re having a hard time with wording, you can choose from a list offered by the AI.

Offer Alternative Word Choices

The thesaurus is every writer’s best friend when they can’t think of the right words to use. ChatGPT can be used to find alternative words and even offer words for a concept you’re thinking of.

For instance, if you have a line that you know will be about a dying leaf on a stick, but you don’t want to use the word "stick," ask ChatGPT for a more attractive synonym.

Assist With Form and Structure

Beyond the words, form and structure are some of the most important elements of a poem. They determine the type of poem it is and how the poem progresses to create an experience for the reader. In other words, the meter, stanza lengths, and rhyme schemes of a poem, just to name a few.

If there’s a particular style of poem you’re looking to write, ChatGPT can give you the guidelines to create it. Additionally, you can ask about rhyme schemes for a poem with a certain amount of lines and choose from the options available.

Frankly, any question you have regarding poetry can be asked and ChatGPT will be able to provide an answer with examples.

Proofread and Edit

Proofreading and editing are such helpful features within ChatGPT , even with poetry. You can copy and paste your newly written poem and ask the AI to check for grammatical errors, spelling mistakes, and other oversights you may have missed.

In terms of editing, though, you’ll want to make sure that ChatGPT doesn’t change your poetry too much. You still want the work to be your own. Additionally, there’s a good chance that the emotions you’ve purposely embedded into the poems will be altered.

Suggestions for Poem Arrangement

In a poetry book, the arrangement of the poems is essential for creating a story—whether there’s a narrative or simply an emotional development. You’ll want your readers to follow along in the book and take something away from it.

It would probably be a bit overwhelming to copy and paste every poem into the search bar and ask ChatGPT to arrange your work. However, you can let the AI know what kind of poems you have and ask for a list of ways to organize them.

In the end, it should be your decision what poem gets placed where.

Guidance With Publication

The publication of a poetry book is a big step for a poet, and there are several questions to ask yourself. Should you consider a full-length poetry book or a chapbook? Are you going to self-publish or attempt to find a publisher?

Though these questions will tend to be more of a personal choice, ChatGPT can help guide you with facts and research. Make sure you give enough information so the answer can be tailored to what you have created.

Assist With Marketing and Promotion

Although ChatGPT can’t promote your book for you, it can offer suggestions for how you can do it successfully. In the search bar, jot down all the information about your book and how to promote it, and see what it spits out for you. It could be anything from creating an effective book ad to marketing yourself on social media.

There are numerous suggestions that can be offered, so if you don’t like what it has given you, or you want more ideas, simply tell ChatGPT that you would like to see more.

Put Your Poetry Out Into the World With the Help of ChatGPT

ChatGPT is a great resource to help with all stages of writing. It can bring ideas to life and test your skills with new writing techniques. When it comes to writing a poetry book, ChatGPT can assist from the initial prompt to the marketing campaign of your self-published chapbook.

Whenever you’re ready to start your poetry book undertaking, test out ChatGPT to see how it can help your process.