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.

About the Author

Monica Becue-Bertaut is an elected fellow of the International Statistical Institute and was named Chevalier des Palmes Academiques by the French Government. She taught statistics and data science at the Universitat Politenica de Catalunya and offered numerous guest lectures on textual data science in different countries. Dr. Becue-Bertaut published several books (in French or Spanish) and work chapters (in English) on this last topic. She also participated in the design of software related to textual data science, such as SPAD.T and Xplortext; being this latter an R package.

Reviews

"Even though textual data science cannot be considered as the youngest sibling of other data science fields, there is still quite a big space to be filled with up-to-date textbooks describing and analyzing various methods and facets of this very interesting topic. In this book, Monica Becue-Bertaut tries to fill this gap, giving theoretical and practical instructions about one of the relatively little known, but powerful methods in textual data science-Correspondence Analysis (CA)... Extensive graphical images and visualizations represented by various types of plot and diagram are used throughout the material, which provides an even better aid to the reader
for grasping the main ideas of the topic... separate mention should be drawn to the language used in the book. It is clear, simple, and even fun to read, providing an
understandable way of covering complex topics... Monica Becue-Bertaut achieved a good blend of theory and practice in her book, which can be used as a handy resource for students and beginners in data science, as well as for specialists in textual data analysis."
- Gia Jgarkava, ISCB December 2019

Book Information
ISBN 9781032093659
Author Monica Becue-Bertaut
Format Paperback
Page Count 212
Imprint Chapman & Hall/CRC
Publisher Taylor & Francis Ltd
Weight(grams) 312g