The algorithmic perception paradox: personalization, news diversity, and trust among young UAE news users

Abstract

Research on algorithmic news personalization remains disproportionately anchored in Western media contexts, leaving the Arab Gulf only thinly theorized. This sequential explanatory mixed-methods study examines how young digital news users in the United Arab Emirates understand personalization, news diversity, and institutional trust. A survey of 300 UAE residents aged 18 to 35 was followed by 20 in-depth semi-structured interviews. Across the quantitative phase, a consistent pattern emerged: stronger perceived personalization was associated with lower perceived diversity and lower trust in online news. TikTok-primary users reported lower perceived diversity than users of YouTube or X, whereas proactive practices such as fact-checking were positively associated with both diversity perceptions and trust. Interview accounts clarified the mechanism behind these associations. Participants valued recommendation systems for their efficiency, yet repeatedly described them as opaque, commercially calibrated, and difficult to contest. The study advances the Algorithmic Perception Paradox as a theoretical concept for explaining how relevance and suspicion can coexist within personalized news environments. Rather than treating this paradox as a local anomaly, the article conceptualizes it as a structural dynamic linking surveillance-capitalist curation to audiences’ lived sense that informational trust depends not only on what is shown, but also on what may be withheld.