Physiological responses to personalized TikTok content: evidence from pupil size and eye blink rate

Personalized social media platforms rely on algorithmic curation to increase user engagement, yet the physiological mechanisms underlying this process are not well understood. This study investigated whether personalized TikTok content influences ocular markers of engagement, specifically pupil size and spontaneous eye blink rate, in a healthy sample. A within-subject design was used in which participants viewed both personalized videos (from their own TikTok feed) and non-personalized videos (from a novel account). Eye tracking was employed to record pupil size and spontaneous eye blink rate during video viewing. Differences between conditions were analyzed using within-subject statistical comparisons. Exploratory analyses examined associations between physiological measures and individual differences, including habitual TikTok use, daily usage duration, follower count, and self-reported enjoyment. Pupil size was significantly larger during personalized compared to non-personalized video viewing, indicating increased arousal-related engagement for personalized content. In contrast, spontaneous eye blink rate did not differ between conditions. Exploratory analyses did not reveal consistent associations between physiological measures and individual usage variables. Viewing personalized TikTok content was associated with larger pupil size than viewing non-personalized content, consistent with increased arousal-related engagement. The absence of differences in eye blink rate suggests that reward-related processes may not be differentially affected by personalization, or that this measure may lack sensitivity in this context. Because personalized and non-personalized feeds inherently differ in the content selected for each user, the present design cannot distinguish the contributions of specific content characteristics, such as emotional intensity and familiarity, to the observed physiological response. With these limitations in mind, the findings highlight the potential of physiological measures, particularly pupillometry, for studying engagement in digital media environments.