A short introduction to computational social science and digital behavioral data

GESIS ›Meet the Experts‹

This talk will provide an introductory overview of the emergence of computational social science (CSS) as a new research area combining multidisciplinary methods and new types of data that promise to be valuable complements to surveys. The term digital behavioral data summarizes a broad variety of data captured by web-based platforms (most prominently platforms for online communication, but also e.g. shopping portals or dating sites) and other digital technologies like smartphones, fitness devices, or RFID sensors. Digital behavioral data result from traces that humans are leaving when using these platforms, i.e. the data is typically not a direct product of a scientifically predesigned research setup.

The talk showcases examples of digital behavioral data and how they have been used in past CSS research to learn about or predict behavior, characteristics, or opinions of platform users. It provides the basis for a series of talks from the area of CSS that will take a closer look at individual strategies for collecting digital behavioral data, different methods data analysis and different use cases for social science research.


 Dr. Katrin Weller  leads the team Social Analytics and Services and is deputy head of the Computational Social Science department at GESIS. She holds a PhD in information science and is interested in understanding scientific communication structures in online environments. Her work also questions data archiving and sharing surrounding social media data. She was Digital Studies Fellow at the US Library of Congress.



GESIS - Leibniz-Institut für Sozialwissenschaften


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