1. Progress feedback for countering selective exposure : when visualization can backfireJanine Riemann, Jasmin Alt, Uroš Sergaš, Marko Tkalčič, Bruce Ferwerda, 2026, published scientific conference contribution Abstract: Selective exposure in online news is often attributed to person- alization mechanisms and user modeling. Recent work proposes interface-level interventions that visualize reading balance or frame cross-cutting exposure as progress. However, we lack empirical evidence on whether alternative representations of user-model feedback meaningfully influence engagement with belief-opposing content. We conducted a between-subject experiment (N = 84) in a controlled news environment comparing two representations of diversity feedback: (1) an analytic bias visualization summarizing viewpoint balance and (2) a metaphorical growth visualization fram- ing cross-cutting exposure as personal development. Across behav- ioral and attitudinal measures of open-minded engagement, neither feedback representation increased engagement relative to control, and the two designs did not differ reliably. Our results suggest that lightweight representations of diversity signals—without adaptive personalization or structural changes to recommendations—may be insufficient to alter selective exposure in single-session settings. We discuss implications for designing user-model feedback and depolarization objectives in recommender systems.
Keywords: human-centered computing, human computer interaction, information systems, recommender systems
Published in RUP: 05.06.2026; Views: 128; Downloads: 7
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2. Game on for news : stance-aware gamification in a news aggregator to promote engagement with diverse viewpointsCaroline Frössling, Uroš Sergaš, Marko Tkalčič, Bruce Ferwerda, 2026, published scientific conference contribution Abstract: Personalized news systems often adapt ranking to user preferences, which can reinforce selective exposure. We investigate an alterna- tive personalization strategy: stance-aware incentive shaping. In- stead of modifying content ranking, we use a minimal per-topic stance user model to adapt reward gradients, awarding more points for engaging with counter-attitudinal content. In a between-subject experiment (� = 98), we compare a non- adaptive baseline with two adaptive incentive framings (levels vs. leaderboards). Stance-aware gamification increased behavioral en- gagement (clicks and time), while subjective engagement and com- prehension did not differ reliably. Only the level-based framing produced significant pre–post increases in stance change and open- minded thinking, with effects varying by topic. We position stance-aware incentive shaping as a lightweight user-model intervention that adapts motivational feedback rather than ranking, offering an alternative pathway for diversity-aware personalization in recommender systems.
Keywords: information systems, recommender systems, personalization, human-centered computing, user studies
Published in RUP: 05.06.2026; Views: 121; Downloads: 8
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5. StreetGamez, a moving projector platform for games : master's thesisPeter Škrlj, 2017, master's thesis Keywords: exergaming, projection, platform, drones, art, pervasive computing, mobile robotics, graphics, gaming, street games, flying displays, drone-assisted art making, content delivery, interactive context-aware projections, user interaction tracking, human-drone interaction
Published in RUP: 09.11.2017; Views: 4346; Downloads: 61
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