Text analysis with R : for students of literature / Matthew L. Jockers, Rosamond Talken.
Material type: TextLanguage: English Series: Quantitative methods in the humanities and social sciencesPublication details: Switzerland : Springer, ©2014. 2020.Edition: 2nd edDescription: xxiii, 277 p. ; col. ill. pbk : 25cmISBN:- 9783030396459
- 9783030396435
- 3030396436
- 3030396428
- 9783030396428
- 3030396444
- 9783030396442
- 3030396452
- 9783030396428
- 9783030396442
- 9783030396459
- Computational linguistics
- R (Computer program language)
- Linguistique informatique
- R (Langage de programmation)
- computational linguistics
- Computational linguistics
- Social research & statistics
- Literature: history & criticism
- Literary studies: general
- Humanities
- Mathematical & statistical software
- Language Arts & Disciplines
- Social Science
- Language Arts & Disciplines
- Literary Criticism
- Computers
- Computers
- Computational linguistics
- R (Computer program language)
- -- Linguistics -- General
- -- Statistics
- -- Library & Information Science -- General
- -- General
- -- Data Processing
- -- Mathematical & Statistical Software
- 006.35 23 JOC
Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
General Books | CUTN Central Library Philosophy & psychology | Non-fiction | 006.35 JOC (Browse shelf(Opens below)) | Available | 46638 |
Includes bibliographical references and index.
Intro -- Preface to the Second Edition -- Preface from the First Edition (Still Relevant) -- Contents -- About the Authors -- List of Figures -- List of Tables -- Part I Microanalysis -- 1 R Basics -- 2 First Foray into Text Analysis with R -- 3 Accessing and Comparing Word Frequency Data -- 4 Token Distribution and Regular Expressions -- 5 Token Distribution Analysis -- 6 Correlation -- 7 Measures of Lexical Variety -- 8 Hapax Richness -- 9 Do It KWIC -- 10 Do It KWIC(er) (and Better) -- Part II Metadata -- 11 Introduction to dplyr -- 12 Parsing TEI XML -- 13 Parsing and Analyzing Hamlet -- 14 Sentiment Analysis -- Part III Macroanalysis -- 15 Clustering -- 16 Classification -- 17 Topic Modeling -- 18 Part of Speech Tagging and Named Entity Recognition -- Appendix A: Variable Scope Example -- Appendix B: The LDA Buffet -- Appendix C: Practice Exercise Solutions -- Index.
This practical introduction explores core R procedures and processes and offers a thorough understanding of the possibilities of computational text analysis at both micro and macro scales. Each chapter concludes with a set of practice exercises.
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