multi dimensional analysis research methods and current issues

Multi-Dimensional Analysis

Research methods and current issues, by tony berber sardinha and marcia veirano pinto.

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Multi-Dimensional Analysis: Research Methods and Current Issues 1st Edition, Kindle Edition

• ISBN-13 978-1350190405
• Edition 1st
• Sticky notes On Kindle Scribe
• Publisher Bloomsbury Academic
• Publication date March 21, 2019
• Language English
• File size 11037 KB
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Editorial Reviews

“The contributors to this volume, leading figures in multi-dimensional analysis, bring in these chapters experience and expertise to enhance existing corpus linguistics resources. The reader will accordingly find both a richness of analysis as well as clarity in explanation of MDA procedures. Essential reading for all researchers using corpus methods who wish to understand how register patterns vary, how the variation may be pinned down, and how such variation relates to underlying situational, social, and cognitive functions.” ― Mike Scott, Visiting Research Fellow in Corpus Linguistics, Aston University, UK “This book is a must-read for anyone who wishes to carry out multi-dimensional analyses of corpora. It consists of a collection of chapters written by experts in the field which take the reader through the origins of the approach and along its different methodological stages, drawing on a range of examples as well as offering a detailed account of existing MD research. It encourages, enlightens and enables future MD analysts.” ― Paul Baker, Professor of English Language, Lancaster University, UK

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• ASIN ‏ : ‎ B07N1C32GQ
• Publisher ‏ : ‎ Bloomsbury Academic; 1st edition (March 21, 2019)
• Publication date ‏ : ‎ March 21, 2019
• Language ‏ : ‎ English
• File size ‏ : ‎ 11037 KB
• Text-to-Speech ‏ : ‎ Enabled
• Screen Reader ‏ : ‎ Supported
• Enhanced typesetting ‏ : ‎ Enabled
• X-Ray ‏ : ‎ Not Enabled
• Word Wise ‏ : ‎ Not Enabled
• Sticky notes ‏ : ‎ On Kindle Scribe
• Print length ‏ : ‎ 428 pages

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ebook ∣ Research Methods and Current Issues

By tony berber sardinha.

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9781350190405

Tony Berber Sardinha

Bloomsbury Publishing

21 March 2019

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Publications

Nini, A., Halvani, O., Graner, L., Gherardi, V., Ishihara, S. Authorship Verification based on the Likelihood Ratio of Grammar Models. https://arxiv.org/abs/2403.08462v1

Ishihara, S., Kulkarni, S., Carne, M, Ehrhardt, S., Nini, A. (2024). Validation in Forensic Text Comparison: Issues and opportunities. Languages , 9(2), 47.   [Open Access]

Nini, A. (2023). A Theory of Linguistic Individuality for Authorship Analysis . Elements in Forensic Linguistics. Cambridge, UK: Cambridge University Press. [Published version] [Twitter thread] [Data and code]

Li, H., Dunn, J., Nini, A. (2022). Register variation remains stable across 60 languages. Corpus Linguistics and Linguistic Theory . [Published version] [Accepted version]

Donlan, L. & Nini, A. (2022). A forensic authorship analysis of the Ayia Napa rape statement. In Picornell, I., Perkins, R., and Coulthard, M. (eds) Methodologies and Challenges in Forensic Linguistics Casework . Hoboken, NJ: Wiley-Blackwell. [Accepted version]

Dunn, J. & Nini, A. (2021). Production vs perception: The role of individuality in usage-based grammar induction. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics , 149-159, Online: Association for Computational Linguistics. [Open access]

Nini, A., Bailey, G., Guo, D., Grieve, J. (2020). The graphical representation of phonological dialect features of the North of England on social media. In Honeybone, P. & Maguire, W. (eds), Dialect Writing and the North of England , 266-296, Edinburgh: Edinburgh University Press. [Accepted version]

Fonteyn, L. & Nini, A. (2020). Individuality in syntactic variation: An investigation of the 17th-century gerund alternation.  Cognitive Linguistics , 31(2), 279-308. [Open access]

Nini, A. (2019). Corpus analysis in forensic linguistics. In Chapelle, C. A. (ed), The Concise Encyclopedia of Applied Linguistics , 313-320, Hoboken: Wiley-Blackwell. [Accepted version]

Grieve, J., Chiang, E., Clarke, I., Gideon, H., Heini, A., Nini, A., Waibel, E. (2019). Attributing the Bixby letter using n-gram tracing.  Digital Scholarship in the Humanities,  34(3), 493-512. [Published version] [Accepted version]

Grieve, J., Montgomery, C., Nini, A., Murakami, A., Guo, D. (2019). Mapping lexical dialect variation in British English using Twitter. Frontiers in Artificial Intelligence,  2, 11. [Open access]

Nini, A. (2019). Developing forensic authorship profiling. Language and Law/Linguagem e Direito,  5(2), 38-58. [Open access]

Nini, A. (2019). The Multi-Dimensional Analysis Tagger. In Berber Sardinha, T. & Veirano Pinto M. (eds),  Multi-Dimensional Analysis: Research Methods and Current Issues , 67-94, London; New York: Bloomsbury Academic. [Accepted version]

Grieve, J., Nini, A., Guo, D. (2018). Mapping lexical innovation on American social media.  Journal of English Linguistics,  46(4), 293-319. [Open access]   [Supplemental Material]

Nini, A. (2018). An authorship analysis of the Jack the Ripper letters.  Digital Scholarship in the Humanities,  33(3), 621-636. [Open access] [Download the Jack the Ripper corpus]

Nini, A. (2017). Register variation in malicious forensic texts. International Journal of Speech, Language and the Law, 24(1), 99-126. [Published version]   [Accepted version]   [Download the Malicious Forensic Text corpus]

Nini, A., Corradini, C., Guo, D., Grieve, J. (2017). The application of growth curve modeling for the analysis of diachronic corpora. Language Dynamics and Change, 7(1), 102-125. [Published version] [Accepted version]

Grieve, J., Nini, A., Guo, D. (2017). Analyzing lexical emergence in Modern American English online. English Language and Linguistics, 21(1), 99-127. [Published version] [Accepted version]

Nini, A. (2015).  Authorship Profiling in a Forensic Context . PhD dissertation. Aston University, Birmingham, UK. [Read]   [Abstract]

Nini, A. (2013). Codal variation theory as a forensic tool. In Bridging the Gap(s) between Language and the Law: Proceedings of the 3rd European Conference of the International Association of Forensic Linguists , 31-41, Porto: Faculdade de Letras da Universidade do Porto. [Open access]

Nini, A. & Grant, T. (2013). Bridging the gap between stylistic and cognitive approaches to authorship analysis using Systemic Functional Linguistics and multidimensional analysis. International Journal of Speech, Language and the Law , 20(2), 173-202. [Published version] [Accepted version]

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The Multi-Dimensional Analysis Tagger

• Linguistics and English Language (L5)

Research output : Chapter in Book/Report/Conference proceeding › Chapter › peer-review

T1 - The Multi-Dimensional Analysis Tagger

AU - Nini, Andrea

M3 - Chapter

SN - 9781350023826

BT - Multi-Dimensional Analysis

A2 - Berber Sardinha, Tony

A2 - Veirano Pinto, Marcia

PB - Bloomsbury Publishing PLC

CY - London; New York

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https://sites.google.com/site/multidimensionaltagger

andreanini/multidimensionalanalysistagger

Folders and files, repository files navigation, the multidimensional analysis tagger v 1.3.3 for windows.

The Multidimensional Analysis Tagger (MAT) is a program that replicates Biber's (1988) Variation across Speech and Writing tagger for the multidimensional functional analysis of English texts, generally applied for studies on text type or genre variation. The program can generate a grammatically annotated version of the corpus selected as well as the statistics needed to perform a text-type or genre analysis. The program plots the input text or corpus on Biber’s (1988) Dimensions and it determines its closest text type, as proposed by Biber (1989) A Typology of English Texts. Finally, the program offers a tool for visualising the Dimensions features of an input text. More information about the tagger can be found in the manual at the official website of MAT: https://sites.google.com/site/multidimensionaltagger

MAT is based on the Stanford Tagger. More information on the Stanford Tagger can be obtained from: http://nlp.stanford.edu/software/tagger.shtml . The Stanford Tagger or a corpus of Stanford Tagger tagged texts is required to run MAT.

When citing the code, please use the following book chapter:

Nini, A. (2019). The Multi-Dimensional Analysis Tagger. In Berber Sardinha, T. & Veirano Pinto M. (eds), "Multi-Dimensional Analysis: Research Methods and Current Issues" , 67-94, London; New York: Bloomsbury Academic. [Download pre-print]

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