Quantitative Corpus Linguistics with R: A Practical Introduction

by Gries; Stefan Th.

• ISBN13: 9780415962704
• ISBN10: 0415962706
• Edition: 1st
• Format: Nonspecific Binding
• Copyright: 2009-02-20
• Publisher: Routledge

Summary

Current corpus linguistics (naturalistic language data) books inform us about what corpus linguistics is, but not HOW to do it. Books addressing R for introductory statitics are also available, however, this is the first textbook on using the programming language R for corpus linguistics. Computational linguists doing corpus work will find R to provide a range of services that currently require several programs to achieve - statistics, graphing, data organization, as well as the language corpus itself.

Author Biography

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

Table of Contents

Acknowledgments	p. viii
Introduction	p. 1
Why Another Introduction to Corpus Linguistics?	p. 1
Outline of the Book	p. 4
Recommendation for Instructors	p. 5
The Three Central Corpus-linguistic Methods	p. 7
Corpora	p. 7
What is a Corpus?	p. 7
What Kinds of Corpora are There?	p. 9
Frequency Lists	p. 12
Lexical Co-occurrence: Collocations	p. 14
(Lexico-) Grammatical Co-occurrence: Concordances	p. 16
An Introduction to R	p. 19
A Few Central Notions: Data Structures, Functions, and Arguments	p. 23
Vectors	p. 28
Basics	p. 28
Loading Vectors	p. 32
Accessing and Processing (Parts of) Vectors	p. 35
Saving Vectors	p. 42
Factors	p. 43
Data Frames	p. 44
Generating Data Frames	p. 44
Loading and Saving Data Frames	p. 46
Accessing and Processing (Parts of) Data Frames	p. 48
Lists	p. 53
Elementary Programming Functions	p. 59
Conditional Expressions	p. 59
Loops	p. 60
Rules of Programming	p. 64
Character/String Processing	p. 68
Getting Information from and Accessing (Vectors of) Character Strings	p. 69
Elementary Ways to Change (Vectors of) Character Strings	p. 70
Merging and Splitting (Vectors of) Character Strings without Regular Expressions	p. 70
Searching and Replacing without Regular Expressions	p. 72
Searching and Replacing with Regular Expressions	p. 79
Merging and Splitting (Vectors of) Character Strings with Regular Expressions	p. 96
File and Directory Operations	p. 99
Using R in Corpus Linguistics	p. 105
Frequency Lists	p. 106
A Frequency List of an Unannotated Corpus	p. 106
A Reverse Frequency List of an Unannotated Corpus	p. 110
A Frequency List of an Annotated Corpus	p. 112
A Frequency List of Tag-word Sequences from an Annotated Corpus	p. 114
A Frequency List of Word Pairs from an Annotated Corpus	p. 118
A Frequency List of an Annotated Corpus (with One Word Per Line)	p. 124
A Frequency List of Word Pairs of an Annotated Corpus (with One Word Per Line)	p. 126
Concordances	p. 127
A Concordance of an Unannotated Text File	p. 127
A Simple Concordance from Files of a POS-tagged (SGML) Corpus	p. 135
More Complex Concordances from Files of a POS-tagged (SGML) Corpus	p. 141
A Lemma-based Concordance from Files of a POS-tagged and Lemmatized (XML) Corpus	p. 146
Collocations	p. 149
Excursus 1: Processing Multi-tiered Corpora	p. 156
Excursus 2: Unicode	p. 166
Frequency Lists	p. 167
Concordancing	p. 169
Some Statistics for Corpus Linguistics	p. 173
Introduction to Statistical Thinking	p. 174
Variables and their Roles in an Analysis	p. 174
Variables and their Information Value	p. 174
Hypotheses: Formulation and Operationalization	p. 176
Data Analysis	p. 182
Hypothesis (and Significance) Testing	p. 183
Categorical Dependent Variables	p. 189
One Categorical Dependent Variable, No Independent Variable	p. 189
One Categorical Dependent Variable, One Categorical Independent Variable	p. 192
One Categorical Dependent Variable, 2+ Independent Variables	p. 200
Interval/Ratio-scaled Dependent Variables	p. 201
Descriptive Statistics for Interval/Ratio-scaled Dependent Variables	p. 201
One Interval/Ratio-scaled Dependent Variable, One Categorical Independent Variable	p. 205
One Interval/Ratio-scaled Dependent Variable, One Interval/Ratio-scaled Independent Variable	p. 211
One Interval/Ratio-scaled Dependent Variable, 2+ Independent Variables	p. 214
Customizing Statistical Plots	p. 215
Reporting Results	p. 215
Case Studies and Pointers to Other Applications	p. 219
Introduction to the Case Studies	p. 219
Some Pointers to Further Applications	p. 220
Appendix	p. 225
References	p. 229
Endnotes	p. 237
Index	p. 243
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