The User Modeling, Adaptation and Personalization (UMAP) conference is considered one of the most prestigious international conferences in the fields of user modeling, personalization, and adaptive intelligent systems. According to the CORE conference ranking, it is classified as an A-category conference.

The award-winning paper, titled "Progress Feedback for Countering Selective Exposure: When Visualization Can Backfire," was developed in collaboration with researchers from Jönköping University, Sweden. The authors are Janine Riemann, Jasmin Alt, Uroš Sergaš, Marko Tkalčič, and Bruce Ferwerda.

The study investigates whether different types of visual feedback about users' news consumption can reduce selective exposure—the tendency for people to favor information that confirms their existing beliefs. The authors compared an analytical visualization of viewpoint balance with a metaphorical "growth" visualization, which presents exposure to opposing viewpoints as a form of personal development. In a controlled experiment involving 84 participants, neither approach significantly increased engagement with content expressing opposing opinions compared with the control group.

These findings suggest that simple visual feedback alone is not sufficient to bring about meaningful changes in users' information-seeking behavior and that more advanced or structural approaches may be necessary.

We sincerely congratulate the award recipients on this outstanding achievement.