Please note: This course will be taught in hybrid mode. Hybrid delivery of courses will include synchronous live sessions during which on campus and online students will be taught simultaneously.
Martijn Schoonvelde is Assistant Professor in European Politics & Society at the University of Groningen. His main research and teaching interests are political communication, political rhetoric, and quantitative text analysis.
With the massive and ever-increasing availability of digital text data, social scientists increasingly use automated text analysis (or “text as data”) to examine various kinds of social and political phenomena. This module introduces participants to a variety of its methods and tools. We discuss their theoretical assumptions, substantive applications of these methods, and their implementation in the R statistical programming language. The meetings – which combine lectures and coding sessions in the RStudio Cloud platform – will be hands-on, dealing with practical issues in each step of a text as data project.
Participants will understand fundamental issues in quantitative text analysis research design such as textual representations, measurement reliability and validation, and prediction accuracy. Participants will learn to convert texts into informative feature matrices and to analyse those matrices using statistical methods. Participants will learn to apply these methods to a text corpus in support of a substantive research question. Furthermore, participants will be able to critically evaluate (social science) research that uses automated text analysis methods.
Familiarity with basic research design and statistical analysis is expected, and familiarity with the R statistical programming language is strongly encouraged.
- Benoit (2020). “Text as Data: An Overview”. Handbook of Research Methods in Political Science and International Relations. Ed. by L. Curini and R. Franzese. Thousand Oaks: Sage: 461–497.
- Welbers, K., Van Atteveldt, W., & Benoit, K. (2017). Text analysis in R. Communication Methods and Measures, 11(4), 245–265.
Background knowledge required:
R = elementary