Becue-Bertaut, Monica

Textual data science with R - Boca Raton CRC Press 2019 - xvii, 194 p. Includes bibliographical references and index - Chapman & Hall/CRC Computer Science & Data Analysis .

Table of contents:

1. Encoding: from a corpus to statistical tables
2. Correspondence analysis of textual data
3. Applications of correspondence analysis
4. Clustering in textual analysis
5. Lexical characterization of parts of a corpus
6. Multiple factor analysis for textual analysis
7. Applications and analysis workflows

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.


R - Computer program language
Computational linguistics
Discourse analysis - Statistical methods
Data processing

401.410285555 / B3T3

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