Look Back – GESIS Fall Seminar in Computational Social Science 2025
From 1 to 26 September 2025, the GESIS Fall Seminar in Computational Social Science took place in Mannheim and online. Apart from live on-site and online courses, it also offered blended learning courses. Overall, participants could choose from ten introductory and advanced courses on computational social science methods and techniques.
Designed to accommodate diverse schedules, our “Introduction to Computational Social Science” courses with both R – taught by Johannes R. Gruber (GESIS Cologne) – and Python – taught by John McLevey (Memorial University) – gave an overview of different methods, techniques, and tools for the collection and analysis of digital behavioral data using a blended learning format that combined guided self-learning phases with live online classroom sessions. Those who wanted to dig deeper into the data collection process could delve into web scraping methods and how to work with APIs in our two live online courses on “Web Data Collection with R and Python”, both facilitated by Iulia Cioroianu (University of Bath). Focusing on the analysis of textual data, Rupert Kiddle (Vrije Universiteit Amsterdam) and Sjoerd Stolwijk (Utrecht University) gave an “Introduction to Machine Learning for Text Analysis in Python.” In “Advanced Methods for Social Network Analysis,” Lorien Jasny (University of Exeter) and teaching assistant Laura Roldan Gomez (University of Exeter) showed participants how to explore statistical network models like ERGMs and SAOMs. Andreu Casas (Royal Holloway, University of London) shared his expertise on “Computer Vision for Image and Video Data Analysis,” teaching participants how to use machine learning to analyze visual data. Daniel Mayerhoffer (University of Amsterdam) provided instructions on simulations for studying complex social phenomena in “Agent-Based Computational Modeling.” Those interested in cutting-edge methods had the chance to learn about word embeddings and state-of-the-art large language models like GPT from Hauke Licht (University of Innsbruck) in “From Embeddings to LLMs: Advanced Text Analysis with Python,” and about how to go beyond prediction to understand causal relationships from Marica Valente (University of Innsbruck) in “Causal Machine Learning.”
Next to the exchange in their respective courses, participants in Mannheim further enjoyed the opportunities for networking at our weekly get-together at GESIS and the dinner at the Rheinterrassen.
Not only the social environment, but also all courses were rated very highly by participants: 9 in 10 participants stated they were (very) satisfied with their course, and a whopping 95% said they would recommend GESIS Training courses. Participants particularly emphasized how engaged the lecturers were, their deep knowledge of the subjects they taught, and their readiness to give individual feedback on participants’ projects. They also appreciated the “really nice environment for learning and asking questions”, that “different approaches were brought into context,” and that the courses were “very practical.” To quote one participant in “Computer Vision for Image and Video Data Analysis”: “Andreu did an excellent job in explaining everything, keeping our attention, making sure everyone understands what he wanted to teach us and was always trying to help.” A big THANK YOU to our fantastic lecturers for their commitment and to our participants for placing their trust in us!
Save the date: The next GESIS Fall Seminar in Computational Social Science will take place from 31 August to 25 September 2026. We will announce the full program in Spring 2026.
