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GESIS Fall Seminar in Computational Social Science (2021)

13 September  - 1 October 2021, Online-Seminar

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 Python (208 kB)
Dr. Orsolya Vásárhelyi, Luis Natera

Introduction to Computational Social Science with Applications in R (169 kB)
Dr. Aleksandra Urman, Max Pellert

Web Data Collection and Natural Language Processing in Python (147 kB)
Indira Sen, Dr. Arnim Bleier, Dr. Roberto Ulloa, Olga Zagovora, Mattia Samory

Automated Web Data Collection (134 kB)
Dr. Theresa Gessler, Hauke Licht

A Practical Introduction to Machine Learning in Python (150 kB)
Dr. Damian Trilling, Dr. Anne Kroon

Social Network Analysis (182 kB)
Dr. Silvia Fierăscu, Ianis Rușitoru