This course provides a practice-oriented introduction to the methods of text mining and quantitative text analysis. In terms of content, the course focuses on primary sources directly or indirectly related to Russia's war against Ukraine and its preconditions. These include speeches by Presidents Volodymyr Zelensky and Vladimir Putin (English translations are available) and the communication of other Russian and Ukrainian political actors – but also political texts from other countries related to the war in Ukraine (e.g. Switzerland, Poland, Germany, USA). The course follows a three-part structure. First, some new academic studies dealing with individual aspects of the political language of the Russo-Ukrainian war will be discussed by way of example. Here, students will have the opportunity to form interdisciplinary teams and develop their own research questions as well as discuss strategies of operationalization and research design (“How can this question be answered in principle using methods of descriptive text analysis?”). Students then receive a practical introduction to the most important functionalities of the programming language R and its intuitive application. Finally, an introduction to the specifics of text analysis follows, always using primary sources as examples. Here, students learn how to prepare and structure text data, analyze it using simple metrics and visualize the results. Students regularly submit code examples and present their solutions. The final paper or seminar paper takes up the research question formulated at the beginning and applies the methods learned to it.
- Enseignant·e: Jan Matti Dollbaum
- Enseignant·e: Pauline Julie Dummermuth