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Results: 473
Number of items: 473
  • Open Access
    Votta, F., Kruschinski, S., Fuglsang Hove, M., Helberger, N., Dobber, T., & de Vreese, C. (2026). Who Do Parties Target? Worldwide Evidence on Political Microtargeting. In A. Burns, G. Enli, A. O. Larsson, J. Y. Robinson, T. Bosch, & K. Kasianenko (Eds.), The Routledge Companion to Social Media and Politics (2nd ed., pp. 215-242). Routledge. https://doi.org/10.4324/9781003359524-17
  • Open Access
    Wang, C., Kroon, A. C., Möller, J., de Vreese, C. H., & Boerman, S. C. (2026). When recommendations are explainable: An eye-tracking study comparing how and what to explain. Information Systems Frontiers, 28(1), 297–315. https://doi.org/10.1007/s10796-025-10670-7
  • Open Access
    Gattermann, K., van den Hoogen, E., & de Vreese, C. (2026). The role of far-right party performance in shaping disinformation concerns of European voters: evidence from the 2024 European Parliament elections. Journal of European Public Policy, 33(2), 636-661. https://doi.org/10.1080/13501763.2025.2489088
  • Open Access
    van Erkel, P. F. A., Van Aelst, P., Hopmann, D. N., de Vreese, C. H., & Van Nieuwenborgh, J. (2026). Building resilience: The influence of the format on the effectiveness of news literacy messages. Journal of Media Literacy Education, 18, 1-21. https://doi.org/10.23860/JMLE-2026-18-1-1
  • Open Access
    Wang, C. (2026). Is explanation the cure? A human-centered framework for explainable recommender systems. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    de León, E., Votta, F., Jongerius, S., Mulder, J., Struminskaya, B., Araujo, T., & de Vreese, C. (2026). Can tailored recruitment messaging increase digital trace data donation compliance? International Journal of Social Research Methodology, 29(4), 503-519. https://doi.org/10.1080/13645579.2025.2568497
  • Open Access
    Weikmann, T., Wouters, F., Tulin, M., Hameleers, M., de Vreese, C., Zarouali, B., & Opgenhaffen, M. (2026). On the same page? Experts are mostly, but not always aligned about disinformation in times of generative AI. Harvard Kennedy School Misinformation Review , 7(2). https://doi.org/10.37016/mr-2020-196
  • Open Access
    Farooq, A., & de Vreese, C. (2026). Deciphering authenticity in the age of AI: how AI-generated disinformation images and AI detection tools influence judgements of authenticity. AI and Society, 41(1), 493-504. https://doi.org/10.1007/s00146-025-02416-5
  • Open Access
    Wouters, F., Weikmann, T., Zarouali, B., Opgenhaffen, M., Hameleers, M., Tulin, M., & de Vreese, C. (2026). The Burden of Truth? Risks of Countering Disinformation in Flanders and the Netherlands. Tijdschrift voor Communicatiewetenschap, 54(2), 198-220. https://doi.org/10.5117/TCW2026.2.004.WOUT
  • Open Access
    Cools, H., & de Vreese, C. H. (2026). From Automation to Transformation with AI-Tools: Exploring the Professional Norms and the Perceptions of Responsible AI in a News Organization. Digital Journalism, 14(5), 791-810. https://doi.org/10.1080/21670811.2025.2505982
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