Textual data science with R
By: Becue-Bertaut, Monica
Material type: 
TextSeries: Chapman & Hall/CRC Computer Science & Data AnalysisPublisher: Boca Raton CRC Press 2019Description: xvii, 194 p. Includes bibliographical references and indexISBN: 9781138626911Subject(s): R - Computer program language | Computational linguistics | Discourse analysis - Statistical methods | Data processingDDC classification: 401.410285555 Summary: 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.
https://www.crcpress.com/Textual-Data-Science-with-R/Becue-Bertaut/p/book/9781138626911
| Item type | Current location | Item location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
| Books | Vikram Sarabhai Library General Stacks | Slot 1319 (0 Floor, East Wing) | Non-fiction | 401.410285555 B3T3 (Browse shelf) | Checked out | 14/04/2021 | 200255 |
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| 401.41 R6 The Routledge handbook of discourse analysis | 401.41 S8R3-II Relating events in narrative Vol.2: typological and contextual perspectives | 401.41 T2W4 What is discourse analysis | 401.410285555 B3T3 Textual data science with R | 401.45 O9 The Oxford handbook of pragmatics | 401.47 F2P6 Political discourse analysis: a method for advanced student | 401.9 V9T4 Thought and Language |
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.
https://www.crcpress.com/Textual-Data-Science-with-R/Becue-Bertaut/p/book/9781138626911
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