GESIS supports the growing interdisciplinary community of Computational Social Science by offering training courses in data science and CSS methods and by providing training materials on central CSS topics and methods.
Among the courses and workshops we run as GESIS trainings are: introduction to R for data analysis, introduction to computational social science with Python/ R, workshops on using social media for social science research, and a fall seminar in computational social science. Please find upcoming courses here; in case of fully booked courses you may want to place yourself on a waiting list.
GESIS CSS researchers give tutorials and hands-on-workshops at international conferences, symposia or summer schools. GESIS has also organized a number of such events, including the ICWSM-16, the IC2S2-17, the European Symposium Series on Societal Challenges in CSS or the Summer School Series on Methods in CSS.
A selection of our teaching materials, videos and Jupyter notebooks:
- 2017–2019 we held three editions of the Summer School on Methods in Computational Social Science, funded by the Volkswagen Foundation; please find a collection of lectures and talks from these events here (videos on Youtube) – Milena Tsvetkova, Ancsa Hannák, Tina Eliassi-Rad, Bruno Ribeiro, Dirk Helbing, Rossano Schiffanella, Alessandro Vespignani, Ciro Cattuto, Andrea Baronchelli, Andreu Casas, Miriam Redi, Yelena Mejova, Jackelyn Hwang, Luca Maria Aiello, Mauro Martino, Sandra González-Bailón, Maximilian Schich, Björn W. Schuller
- Tutorial at ACM FAT* Conference 2020 on the Error Framework for Digital Traces of Humans (video on Youtube) – Indira Sen, Fabian Flöck, Katrin Weller, Bernd Weiß and Claudia Wagner
- Videos and slides (in German) on Data Scraping with Python (video on Youtube) – Carsten Schwemmer
- Lecture Reading cross-cultural relations from Wikipedia (video on Youtube) – Fabian Flöck
- Lecture Gathering Knowledge from User Generated Content (video on Youtube) – Claudia Wagner
- Jupyter Notebook Workshop: Practical Introduction to Text Mining (on GESIS Notebooks) – Andreas Niekler and Arnim Bleier
- Jupyter Notebook Social Network Analysis in R (on Github)– Julian Kohne
- Binder Notebook Short introduction on NLP with spaCy (on Github)– Mattia Samory
We are happy if you find this valuable for your work; please remember to credit the authors and cite appropriately.