Aarhus University Seal

DATALAB

  • Center for Digital Social Research

About DATALAB


DATALAB – Center for Digital Social Research is an interdisciplinary research center established in 2016 under the School of Communication and Culture at Aarhus University, Denmark. Led by Professor Anja Bechmann, the center conducts forefront research on algorithmic communication platforms and citizens, collectives, and populations in datafied societies. The center focuses on AI-powered platforms, associated socio-technical actors, patterns of agency and influence, and effects on communication flows. 

DATALAB hosts fundamental research projects that are theoretically based, empirically tested, and often including large-scale trace data. Our research has also contributed to informing decisions on policy and regulatory frameworks (e.g. in relation to platforms and AI). The projects at the center utilize a wide range of methods from computational social science often combining learning models with experiments, surveys, digital ethnography, and interviews.   

DATALAB researchers and projects share a vision and fundamental interest in creating novel methods and reinterpreting theories to better understand platforms and the modern techno-social fabric. Our projects provide novel knowledge on algorithmic and data-driven agency and societies with a particular sensitivity towards principles of democracy, human rights, and ethics.


Contact


Anja Bechmann

Center Director
anjabechmann@cc.au.dk
+45 5133 5138





Recent Publications


Sort by: Date | Author | Title

Lunding, R. S., Lunding, M. S., Feuchtner, T., Petersen, M. G., Grønbæk, K. & Suzuki, R. (2024). RoboVisAR: Immersive Authoring of Condition-based AR Robot Visualisations. In HRI '2024: Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (pp. 462-471). Association for Computing Machinery. https://doi.org/10.1145/3610977.3634972
Tommasel, A. & Assent, I. (2024). Semantic grounding of LLMs using knowledge graphs for query reformulation in medical information retrieval. In W. Ding, C.-T. Lu, F. Wang, L. Di, K. Wu, J. Huan, R. Nambiar, J. Li, F. Ilievski, R. Baeza-Yates & X. Hu (Eds.), 2024 IEEE International Conference on Big Data (BigData) (pp. 4048-4057). IEEE. https://doi.org/10.1109/BigData62323.2024.10826117, https://doi.org/10.1109/BigData62323.2024.10826117
Schreibman, S., Ping Huang, M. & Kuzman Šlogar, K. (2024). Social Justice in Digital Humanities. Interactive production, #dariahTeach. https://teach.dariah.eu/
Koch, A. K., Mønster, D. & Nafziger, J. (2024). Spillover effects of reminder nudges in complex environments. Proceedings of the National Academy of Sciences (PNAS), 121(17), e2322549121. Article e2322549121. https://doi.org/10.1073/pnas.2322549121

Latest activities



Latest Media Apperances