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Text analysis with R : for students of literature / Matthew L. Jockers, Rosamond Talken.

By: Contributor(s): Material type: TextTextLanguage: 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
Subject(s): Additional physical formats: Print version:: Text analysis with R.DDC classification:
  • 006.35 23 JOC
Online resources:
Contents:
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.
Summary: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode
General Books 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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