Computational Social Science (CSS)
The department CSS collects digital behavioral data and provides computer-based methods for collecting and analyzing such data for social science research. It also supports scientists with the integration of digital behavioral data into their research designs. The department's research focuses on the quality of digital behavioral data, the development and validation of computational social science methods and the transformation of digital societies.
Our Services
GESIS Consulting on DBD
Here you can get advice on computational social science methods and digital behavioral data. We will be happy to help you!
GESIS Guides to DBD
We have compiled informative overviews, introductions and examples of good practices to help you.
Our Teams
Data Science Methods
The team Data Science Methods focuses on the design, implementation, and evaluation of data-driven methods for computational social science (CSS), especially Natural Language Processing, Machine Learning and Network Science Methods. The team aims to push the state-of-the-art to improve how we describe, quantify, and explain sociotechnical phenomena with digital behavioral data (DBD).
Transparent Social Analytics
The team Transparent Social Analytics aims to make collection, preprocessing and analysis methods for digital behavioral data (DBD) accessible and transparent and computational social science (CSS) research reproducible. The team achieves this by (i) conducting research on computational social science methods and workflows, while strictly following open science principles; and (ii) offering services that support social scientists in making their research reproducible.
Designed Digital Data
The team Designed Digital Data develops services to support the collection of high quality, longitudinal digital behavioral data (DBD). Service infrastructures will specifically be designed to combine DBD with survey data to enable innovative social science research. In addition to developing services such as a Smartphone App, an Online Access Panel and a web tracking tool, the team engages with related methodological, technical and ethical challenges.
Digital Society Observatory
The team Digital Society Observatory aims at observing society through the lens of Digital Behavioral Data (DBD) with a focus on data that can be collected from different online platforms. One goal of the team is to release datasets that enable researchers to capture, analyze, and explain the facets of digital society and the impact of socio-technical systems. The team also coordinates the trainings, guidelines, and consultancy activities from the Computational Social Science (CSS) department. With these community-oriented services we want to better equip researchers with the means for studying societal phenomena with CSS methods and DBD.The team aims at observing society through the lens of DBD with a focus on data that can be collected from different online platforms. One goal of the team is to release datasets that enable researchers to capture, analyze, and explain the facets of digital society and the impact of socio-technical systems. The team also coordinates the trainings, guidelines, and consultancy activities from the CSS department. With these community-oriented services we want to better equip researchers with the means for studying societal phenomena with CSS methods and DBD.
