Corpus Linguistics and Statistics with R

1. Front Matter

   Pages i-xiii

   PDF

2. Introduction

   • Guillaume Desagulier

   Pages 1-12

3. Part I

   1. Front Matter

      Pages 13-14

      PDF

   2. R Fundamentals

      • Guillaume Desagulier

      Pages 15-49

   3. Digital Corpora

      • Guillaume Desagulier

      Pages 51-67

   4. Processing and Manipulating Character Strings

      • Guillaume Desagulier

      Pages 69-86

   5. Applied Character String Processing

      • Guillaume Desagulier

      Pages 87-114

   6. Summary Graphics for Frequency Data

      • Guillaume Desagulier

      Pages 115-135

4. Part II

   1. Front Matter

      Pages 137-138

      PDF

   2. Descriptive Statistics

      • Guillaume Desagulier

      Pages 139-149

   3. Notions of Statistical Testing

      • Guillaume Desagulier

      Pages 151-195

   4. Association and Productivity

      • Guillaume Desagulier

      Pages 197-238

   5. Clustering Methods

      • Guillaume Desagulier

      Pages 239-294

5. Back Matter

   Pages 295-353

   PDF

This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.

• R package linguistics
• categorical data
• clustering methods
• data organization
• frequency data
• linguistics with R
• modeling
• quantitative methods for linguistics
• regression methods
• statistics for linguistics
• textual data analysis

“The fine expository qualities of CLSR, together with the sheer enthusiasm and generosity of its author, do everything to encourage its readers to use the rich and various resources R makes available to explore and discover new ways of addressing familiar problems.” (Graham Ranger, Corpora, Vol. 14 (2), 2019)

• Université Paris 8, Saint Denis, France

  Guillaume Desagulier

Guillaume Desagulier is an Associate Professor of English grammar and linguistics at Paris 8 University and President of the French Cognitive Linguistics Association (2015-).

Policies and ethics