Textual data science with R
Author(s)
Bibliographic Information
Textual data science with R
（Series in computer science and data analysis）
CRC Press, c2018
- : hardback
Available at 5 libraries
Note
"A Chapman & Hall book"
Includes bibliographical references (p. 189-190) and index
Description and Table of Contents
Description
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.
Table of Contents
Coding: From Corpus to Statistical Tables. Correspondence Analysis Applied to Textual Data. Clustering in Textual Analysis. Lexical Characteristics of the Parts of a Corpus. Multiple Tables in Textual Analysis. Analysis Strategy through Applications.
by "Nielsen BookData"