11 September - 29 September 2023, GESIS Mannheim
The GESIS Fall Seminar in Computation 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.
Introduction to Computational Social Science with R
Aleksandra Urman, Max Pellert
Automated Image and Video Analysis with Python
Andreu Casas, Felicia Loecherbach
Automated Web Data Collection with Python
Felix Soldner, Jun Sun, Leon Froehling
Automated Web Data Collection with R
Allison Koh, Hauke Licht
From Embeddings to Transformers: Advanced Text Analysis with Python
Hauke Licht, Jennifer Victoria Scurrell
Introduction to Machine Learning for Text Analysis with Python
Damian Trilling, Anne Kroon
Social Network Analysis with R
Michal Bojanowski
