In the digital age, plenty of digital traces is readily available for social scientific inquiry. A large share of these traces is textual data. Due to their sheer size, a qualitative research strategy is often not suitable. Social scientists can, however, use automated, quantitative methods to derive information from text data to answer social-scientific questions. This course will introduce students to text mining methods in a theoretical and practical manner. Students will learn about the underpinnings and social scientific applications of quantitative text analysis and how to perform them in R. Hence, students should have a basic understanding of R (e.g., acquired through the introductory statistics course). For examination, students will use the methods in empirical projects that deal with a social-scientific question from the realm of political sociology. En detail, students will form groups that try to replicate existing findings using new, textual data. The course will be split into thematic blocks, dealing with logic of using text for social-scientific inquiry, text preprocessing, analysis, and the presentation of preliminary results. The exam will be held in German or English.
- Trainer/in: Felix Lennert