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Social Media Influence

  •  A large-scale study of social media as infrastructures of influence in national populations with a focus on false information

Social Media Influence Project (1/09/2023 - 29/02/2028)
Funding: DKK 6.2 million by Independent Research Fund Denmark


Participants: Bechmann, Anja (PI), Holt, Anton Elias, Wegmann, David Josias, Walter, Jessica Gabriele, Brems, Miriam, Nielbo, Kristoffer Laigaard (CoPI), Baglini, Rebekah Brita (CoPI)


Increased use of social media comes at a societal price when influential actors, and the patterns of how and who they influence are hidden. When such patterns and structures are hidden, it prevents effective mitigation against their potentially harmful impact on trust and well-being in democratic societies. The project creates novel knowledge on this topic by studying social media as infrastructures for influence in national populations. The focus of the project on false information serves as a critical case for understanding influence, which becomes especially relevant in times of crisis and with social media's increasing role as an information source. The major contributions of the project are reconfiguring theoretical concepts for the analysis of social media influence, along with novel and innovative scalable methods and code to analyze influence and influential actors. In addition, the project contributes with empirical findings for a better understanding of information disorders by analyzing two main sources: 1) Facebook trace data from 28 European countries at a national scale, and 2) the YouTube watch-histories of 1,000 Danish citizens over 4.5 years. By analyzing the data in relation to citizens’ socio-demographic backgrounds, psychological profiles, measured and perceived influence, the project advances our understanding of social media influence.

Subprojects:



Associated publications

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Baglini, R. & Bar-Asher Siegal, E. A. (2025). Modeling linguistic causation. Linguistics and Philosophy, 48(4), 647-691. https://doi.org/10.1007/s10988-025-09436-w
Feldkamp, P., Kardos, M., Nielbo, K. L. & Bizzoni, Y. (2025). Modeling Multilayered Complexity in Literary Texts. In Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025) (pp. 142). Association for Computational Linguistics. https://aclanthology.org/2025.nodalida-1.15/
Feldkamp, P., Bizzoni, Y., Jacobsen, M., Thomsen, M. R. & Nielbo, K. L. (2025). The Goodreads’ ›Mediocre‹: Assessing a Grey Area of Literary Judgements. In Weder Fail noch Lobgesang. Nichteindeutige Wertung von Literatur im digitalen Raum Forschungsverbund Marbach Weimar Wolfenbüttel. https://doi.org/10.17175/SB006_002

Associated activities


Associated media apperances