Analyzing Digital Behavioral Data

Social media data and other digital behavioral data (DBD) are important for analyzing social science topics in digital societies and for understanding the evolvement of socio-technical systems. GESIS offers methodological insights on how computational methods support social science research and off-the-shelf tools for mining social entities, enriching data and disclosing social structures.

The "Total Error Framework for Digital Traces of Human Behavior on Online Platforms" (TED-On) is our first step in building a comprehensive framework for systematic error detection in the collection, processing, and analysis of digital behavioral data.

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GESIS Methods Hub

The Methods Hub is a collaborative online platform dedicated to advancing social science research by sharing computational methods and related tutorials for using, managing, and enriching digital behavioral data (DBD).

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Consulting on Digital Behavioral Data
Do you need further advice on digital behavioral data? Our experts will be happy to advise you personally and individually on topics relating to the collection, analysis and visualization of digital behavioural data.

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Open Science
We support and implement Open Science. Please visit our work on GitHub.

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