Chapter 1: Calculating with Letters
Chapter 2: Using R for Text Analysis
Chapter 3: Text as Data: Obtaining, Preparing, and Cleaning
Chapter 4: Extracting and Visualising Information from Text
Chapter 5: Supervised Machine Learning for Text Data
Chapter 6: Unsupervised Machine Learning for Text Data
Chapter 7: Evaluation and Validation of Quantitative Text Analysis
Chapter 8: Using Python within R for QTA
Chapter 9: Communicating Text Analysis

This book is for social science students who need to learn the theory of analysis alongside the specifics of the R software package.

Julian Bernauer is a Researcher and permanent Scientific Staff at the Mannheim Centre of European Social Research (MZES), University of Mannheim. His interest in QTA started in 2006, when he wrote a master thesis supervised by Prof. Thomas Bräuninger at the University of Konstanz (where he studied Politics and Public Management) analysing speeches of members of the German parliament. The topic of this research and his doctoral studies at the University of Konstanz (finished in 2012) was political representation of different sorts, and he moved on to lecture and study comparative political institutions as a Postdoctoral Researcher and Lecturer (Oberassistent) at the University of Bern. Since 2017, he is a member of the Mannheim Centre of European Social Research (MZES), first as staff in the Data and Methods Unit (DMU), and since 2020 as permanent Scientific Staff and Researcher in the institute's IT department. He is also involved in the management of the MZES.