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!

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GESIS Guides to DBD

We have compiled informative overviews, introductions and examples of good practices to help you.

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GESIS AppKit

The GESIS AppKit enables the smartphone-based collection of survey and sensor data.

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GESIS Web Tracking

GESIS Web Tracking enables the browser-based collection of digital behavioral data.

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Our Teams

The Team Data Science Methods works at the intersection between Natural Language Processing (NLP) and social science, with a specific focus on research questions at the interface between computational argumentation and computational social science/political communication. We develop methods which integrate multiple information sources (i.e., socio-demographic features, attitudes and values of speakers and audiences; textual properties) and address recent challenges in NLP (modeling subjective phenomena and disagreement; low-resource scenarios; bias).

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.

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.

The services and research of the Team Digital Society Observatory focus on the observation of society through the lens of digital behavioral data, with a particular emphasis on data collected from online platforms. The main services allocated to the team are the Web Data service, the Guides to Digital Behavioral Data, and the Consulting on Computational Social Science Methods and Digital Behavioral Data. The team conducts substantive and methodological research on digital society and the tools that can be used to study it.