Quantitative Corpus Linguistics with R: A Practical Introduction, 2nd Edition (Hardback) book cover

Quantitative Corpus Linguistics with R

A Practical Introduction, 2nd Edition

By Stefan Th. Gries


274 pages

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As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on:

  • data processing and manipulation in general;
  • text processing with and without regular expressions of large bodies of textual and/or literary data, and;
  • basic aspects of statistical analysis and visualization.

This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.

Table of Contents

Chapter 1. Introduction

Chapter 2. The Four Central Corpus-Linguistic Methods

Chapter 3. An Introduction to R

Chapter 4. Some Basic Statistical Notions and Tests

Chapter 5. Using R in Corpus Linguistics: Case Studies

Chapter 6. Next steps

About the Author

Stefan Th. Gries is Professor of Linguistics at University of California, Santa Barbara, USA.

Subject Categories

BISAC Subject Codes/Headings:
EDUCATION / Teaching Methods & Materials / Arts & Humanities
LANGUAGE ARTS & DISCIPLINES / Linguistics / General
MATHEMATICS / Probability & Statistics / General