Text Analytics for Corpus Linguistics and Digital Humanities: Simple R Scripts and Tools (Language, Data Science and Digital Humanities)
Language: English
Published by Bloomsbury Academic, 2024
- Hardcover
- New

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- Title
- Text Analytics for Corpus Linguistics and Digital Humanities: Simple R Scripts and Tools (Language, Data Science and Digital Humanities)
- Author
- Schneider, Gerold
- Publisher
- Bloomsbury Academic
- Publication year
- 2024
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1350370827
- ISBN 13
- 9781350370821
Do you want to gain a deeper understanding of how big tech analyses and exploits our text data, or investigate how political parties differ by analysing textual styles, associations and trends in documents? Or create a map of a text collection and write a simple QA system yourself?
This book explores how to apply state-of-the-art text analytics methods to detect and visualise phenomena in text data. Solidly based on methods from corpus linguistics, natural language processing, text analytics and digital humanities, this book shows readers how to conduct experiments with their own corpora and research questions, underpin their theories, quantify the differences and pinpoint characteristics. Case studies and experiments are detailed in every chapter using real-world and open access corpora from politics, World English, history, and literature. The results are interpreted and put into perspective, pitfalls are pointed out, and necessary pre-processing steps are demonstrated. This book also demonstrates how to use the programming language R, as well as simple alternatives and additions to R, to conduct experiments and employ visualisations by example, with extensible R-code, recipes, links to corpora, and a wide range of methods. The methods introduced
can be used across texts of all disciplines, from history or literature to party manifestos and patient reports.
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About the Author
Mikko Laitinen is Professor of English Language at the University of Eastern Finland, Finland
Martin Schweinberger is Lecturer in Applied Linguistics at the University of Queensland, Australia, and Co-Director of the Language Technology and Data Analysis Laboratory (LADAL). A quantitative corpus linguist, Martin specializes in computational analyses of text and speech, aiming to bridge computational and corpus linguistics. He is a Chief Investigator of the Language Data Commons of Australia (LDaCA), a national research infrastructure project funded by the Australian Research Data Commons (ARDC) and National Collaborative Research Infrastructure Strategy (NCRIS). Martin is also currently serving as Vice-President Profession of the International Society for the Linguistics of English (ISLE) and he is a re-elected board member of the International Computer Archive of Modern and Medieval English (ICAME). Martin is Associate Editor of the Australian Review of Applied Linguistics and he has published widely in various high-impact journals such as Lingua, English World-Wide, or Big Data & Society. His research areas include language variation and change, socio-pragmatics, discourse markers and particles, vulgarity, L1 & L2 acquisition, computational modelling, and best practices in the language sciences.
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