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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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Cao, Z., Zhao, X., Krieger, L., Scharr, H. & Assent, I. (2025). LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching. Poster session presented at The Thirty-ninth Annual Conference on Neural Information Processing Systems, San Diego, California, United States.
Pauli, A. B., Augenstein, I. & Assent, I. (2025). Measuring and Benchmarking Large Language Models’ Capabilities to Generate Persuasive Language. In L. Chiruzzo, A. Ritter & L. Wang (Eds.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 10056-10075). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.naacl-long.506
Pauli, A. B., Augenstein, I. & Assent, I. (2025). Mind the Style Gap: Meta-Evaluation of Style and Attribute Transfer Metrics. In C. Christodoulopoulos, T. Chakraborty, C. Rose & V. Peng (Eds.), EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025: EMNLP 2025 (pp. 21550-21564). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.findings-emnlp.1175

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