5 September - 23 September 2022, 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.
Week 1 (05-09 September)
Introduction to Computational Social Science with R (210 kB)
Aleksandra Urman, Max Pellert
Introduction to Computational Social Science with Python (152 kB)
Milena Tsvetkova, Patrick Gildersleve
Tools for Efficient Workflows, Smooth Collaboration and Optimized Research Outputs (157 kB)
Julia Schulte-Cloos, Lukas Lehner
Week 2 (12-16 September)
Automated Web Data Collection with R (152 kB)
Theresa Gessler, Hauke Licht
Automated Web Data Collection with Python (151 kB)
Felix Soldner, Jun Sun, Leon Froehling
Big Data Management and Analytics (143 kB)
Rainer Gemulla, Adrian Kochsiek
Week 3 (19 - 23 September)
Network Analysis in R (143 kB)
David Schoch, Termeh Shafie
Introduction to Machine Learning for Text Analysis with Python (149 kB)
Damian Trilling, Anne Kroon
Automated Image and Video Data Analysis with Python (220 kB)
Andreu Casas, Felicia Loecherbach