Indira Sen, Summer 2024, Uni Konstanz

Computational Social Science (CSS) provides a broad approach to the analysis of human attitudes, behavior, and characteristics through computational approaches. CSS integrates the implementation of data retrieval and processing, the application of statistical analysis methods, and the interpretation of results to derive insights into human behavior at high resolutions and large scales.

This hand-son, project-based seminar introduces a set of examples of research projects in CSS as introductory lectures. Students build on those lectures to work on research projects in small groups under the guidance of the lecturer. These projects include the motivation of a research question, the design of a project to assess it, as well as data analysis. Students can take the seminar along with the course "Social Media Data Analysis" to apply the methods they learn in the course as part of their projects.

• use digital trace data to answer social research questions
• develop computational models for large-scale analysis of digital trace data
• perform statistical analysis for empirical social research

Apr 8: Introduction
Apr 15: Examples of CSS Research
Apr 22: Description of Projects and Datasets
May 13: Techniques for Exploratory Data Analysis
Jun 3: Text-as-Data Methods
Jun 10: Network Analysis Methods
Jun 17: Reproducible Research Pipeline
Jun 24: Project Guidance and Discussion
Jun 27: project registration deadline
Jul 1: Project Guidance and Discussion
Jul 8: Project Guidance and Discussion
Jul 15: Project Guidance and Discussion
Jul 22: Midway Presentations
Jul 29: Project Guidance and Discussion
mid-August (exact date TBD): Final Presentations
end-August (exact date TBD): Final Reports Due