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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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Vicente, C. R., Assent, I. & Jensen, C. S. (2011). Effective Privacy-Preserving Online Route Planning. In 2011 12th IEEE International Conference on Mobile Data Management (MDM) (pp. 119-128). IEEE Computer Society Press. https://doi.org/10.1109/MDM.2011.20
Assent, I. (2011). Efficient algorithms for collaborative decision making for large scale settings. In Proceedings of the 3rd international workshop on Collaborative information retrieval (pp. 15-18). Association for Computing Machinery. https://doi.org/10.1145/2064075.2064081
Kremer, H., Günnemann, S., Ivanescu, A.-M., Assent, I. & Seidl, T. (2011). Efficient Processing of Multiple DTW Queries in Time Series Databases. Lecture Notes in Computer Science, 6809, 150-167. https://doi.org/10.1007/978-3-642-22351-8_9
Roepstorff, A. (2011). Eksperimentel Antropologi. Tidsskriftet Antropologi, 63.

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