Quantitative Text Analysis Using R

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 Braeuninger 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. Anna Wohlmann is a doctoral candidate at the Technical University of Munich, holding a Master's degree in Politics & Technology from the Technical University of Munich and a Bachelor's degree in Political Science with a minor in Psychology from the University of Mannheim. When introduced to QTA with R in a bachelor-seminar, Anna immediately knew this would be their method of choice. The analysis of social media content created by social movements is the main focus of Annas research.

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