GESIS Fall Seminar in Computational Social Science 2024
30 August - 27 September 2024, GESIS Mannheim
The GESIS Fall Seminar in Computational Social Science targets social scientists, data scientists, and researchers in the digital humanities that collect and analyze data from the web, social media, or digital text archives. Its one-week courses are taught by both GESIS and international experts and cover methods and techniques for collecting and analyzing digital behavioral data (“big data”), for example Machine Learning or Text Mining using both R and Python. Lectures in each course are complemented by hands-on exercises giving participants the opportunity to apply these methods to data. All courses are held in English.
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Week 1 (30 August-05 September)
Week 1 (30 August-05 September)
Introduction to Computational Social Science with R (126 kB)
Johannes B. Gruber
Introduction to Computational Social Science with Python (125 kB)
John McLevey
Week 2 (09-13 September)
Week 2 (09-13 September)
Web Data Collection with R and/or Python (152 kB)
Iulia Cioroianu
Week 3 (16-20 September)
Week 3 (16-20 September)
Introduction to Social Network Analysis with R (107 kB)
Philip Leifeld
Agent-based Computational Modeling (129 kB)
Michael Mäs, Fabio Sartori
Introduction to Machine Learning for Text Analysis with Python (166 kB)
Marieke van Hoof, Rupert Kiddle
Week 4 (23-27 September)
Week 4 (23-27 September)
Advanced Social Network Analysis with R (166 kB)
Michał Bojanowski
Automated Image and Video Analysis with Python (156 kB)
Andreu Casas, Felicia Loecherbach
From Embeddings to LLMs: Advanced Text Analysis with Python (221 kB)
Hauke Licht, Lisa Maria Lechner