In the course of datafication, social scientists are confronted with the increasing availability of digital behavioral data (DBD). Social media platforms, mobile apps, and sensors offer rich insights into human behavior, but these new data sources come with significant challenges in terms of quality. To address these issues, the two-day workshop “Tools – Indicators – Metrics: Data Quality in Computational Social Science” (December 11 -12, 2024) brought together experts in the field to discuss ways to measure, assess, and improve the quality of digital behavioral data. The workshop was organized as part of the Competence Center Data Quality in the Social Sciences (KODAQS). It combined formats for expert inputs via keynote speeches, presentations of different case studies on existing tools and workflows, and interactive breakout sessions.
New post on the GESIS Blog: Peters, Shah and Weller write about the challenges of dealing with new data sources
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