28542
Lehrforschungsprojekt
Introduction to computational social science
Yangliu Fan
Comments
In the contemporary age, our digital routines generate sequences of continuous interactions across multiple channels, platforms, and devices – leaving behind thousands of digital traces. The possibility of gathering and analyzing such data can transform the empirical basis for communication research. This course introduces the methods and logic of computational social science – an emerging field that employs computational methods to study social phenomena. Students will learn to work with large-scale digital data using Python and to apply, interpret, and validate two families of methods: network analysis and computational textual analysis (including large language models).
The course will work through each family of methods in turn, pairing theoretical knowledge with hands-on applications. By the end of the course, students will have experience analyzing large-scale data and will have developed practical methodological skills for designing and conducting their own empirical projects. A strong interest in empirical work and a basic knowledge of mathematics are required. No prior programming experience is required.
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16 Class schedule
Regular appointments
Mon, 2026-10-12 12:00 - 14:00
Mon, 2026-10-19 12:00 - 14:00
Mon, 2026-10-26 12:00 - 14:00
Mon, 2026-11-02 12:00 - 14:00
Mon, 2026-11-09 12:00 - 14:00
Mon, 2026-11-16 12:00 - 14:00
Mon, 2026-11-23 12:00 - 14:00
Mon, 2026-11-30 12:00 - 14:00
Mon, 2026-12-07 12:00 - 14:00
Mon, 2026-12-14 12:00 - 14:00
Mon, 2027-01-04 12:00 - 14:00
Mon, 2027-01-11 12:00 - 14:00
Mon, 2027-01-18 12:00 - 14:00
Mon, 2027-01-25 12:00 - 14:00
Mon, 2027-02-01 12:00 - 14:00
Mon, 2027-02-08 12:00 - 14:00