Text Analysis with R : For Students of Literature. 2nd ed. 2020

種類:

電子ブック

責任表示:

by Matthew L. Jockers, Rosamond Thalken

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Jockers, Matthew L.
• Thalken, Rosamond.
• SpringerLink (Online service)

シリーズ名:

Quantitative Methods in the Humanities and Social Sciences ;

ISBN:

9783030396435 [3030396436]    

注記:

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 by Chapter -- 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 -- Appendices -- Index -- List of Tables -- List of Figures.
Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. Text Analysis with R is written with

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