Textual Data Science with R

Mónica Bécue-Bertaut is an elected fellow of the International Statistical Institute and was named Chevalier des Palmes Académiques by the French Government. She taught statistics and data science at the Universitat Politènica de Catalunya and offered numerous guest lectures on textual data science in different countries. Dr. Bécue-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.

"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, Mónica Bécue-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 readerfor 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 anunderstandable way of covering complex topics... Mónica Bécue-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

• 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.