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Computational Social Science

The mission of the Computational Social Science (CSS) department is to support scientists that aim to work with digital behavioral data (DBD) to learn about social and socio-technical phenomena. Digital behavioral data are digital observations of human and algorithmic behavior which are, amongst others, recorded by online platforms (like Google, Facebook), devices (like smartphones, RFID sensors, satellites or street view cameras) or dedicated software (browser extensions, mobile usage apps). We support scientists in the different phases of their research ranging from the planning and design of a study to the data collection, the data analysis and the documentation. We follow open science principles and help other CSS researchers to comply with these principles.

Our Services

Our Teams

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).

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 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.