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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


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Bøgh, K. S., Chester, S., Sidlauskas, D. & Assent, I. (2017). Template Skycube Algorithms for Heterogeneous Parallelism on Multicore and GPU Architectures. In SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data (pp. 447-462). Association for Computing Machinery. https://doi.org/10.1145/3035918.3035962
Heimann, K., Fusaroli, R., Gonzalez de la Higuera Rojo, S., Johannsen, N. N., Riede, F., Fay, N., Lombard, M. & Tylén, K. (2017). The adaptive evolution of early human symbolic behavior. In R. Granger, U. Hahn & R. Sutton (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society: CogSci 2017 (pp. 494). Cognitive Science Society. https://mindmodeling.org/cogsci2017/papers/0100/paper0100.pdf
Bechmann, A. (2017). The Algorithmic Gaze: Predicting Uploader's Gender Based on Private Social Media Images. Paper presented at AOIR 2017 Networked Publics, Tartu, Estonia.
Mitkidis, P., Ayal, S., Shalvi, S., Heimann, K., Levy, G., Kyselo, M., Wallot, S., Ariely, D. & Roepstorff, A. (2017). The effects of extreme rituals on moral behavior: The performers-observers gap hypothesis. Journal of Economic Psychology, 59, 1-7. https://doi.org/10.1016/j.joep.2016.12.007

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