Corpus Linguistics and Statistics with R: Introduction to Quantitative Methods in Linguistics

by Guillaume Desagulier

Overview

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.

Product Details

ISBN-13:	9783319645704
Publisher:	Springer International Publishing
Publication date:	11/19/2017
Series:	Quantitative Methods in the Humanities and Social Sciences
Edition description:	1st ed. 2017
Pages:	353
Product dimensions:	7.01(w) x 10.00(h) x (d)

About the Author

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

Table of Contents

Introduction.- R Fundamentals.- Digital Corpora.- Processing and Manipulating Character Strings.- Applied Character String Processing.- Summary Graphics for Frequency Data.- Descriptive Statistics.- Notions of Statistical Testing.- Association and Productivity.- Clustering Methods.

Editorial Reviews

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)

From the Publisher