Compass: Continuously Aligning Social Media Feeds via In-Situ Reflections

Abstract:Social media recommendation feeds often optimize for users' immediate impulses rather than preferences they would hold after deeper reflection. Some systems address this misalignment by incorporating users' explicit preferences via a configuration page or in-feed controls instead of just behavioral signals. However, users typically have evolving preferences, and their stated preferences and behavior naturally diverge, necessitating continuous reflection and feed realignment. But existing strategies require the user to take initiative and are often effortful; as a result, in practice they are rarely invoked. We present Compass, a system that aligns a user's feed with their reflective preferences by helping users reflect on and articulate their preferences given their behavior. To enable continuous reflection during everyday browsing, Compass surfaces in-situ reflections via lightweight notifications, while feed alignment is achieved by periodically simulating behavioral signals and directly manipulating feed content. We embedded Compass within YouTube Shorts and compared it against a baseline without continuous support through a 10-day field study (N=15). We found that Compass promoted more reflective and purposeful feed consumption, iterative preference adjustment, and stronger feed alignment, without sacrificing the casual nature of feed browsing.

Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)

arXiv:2608.04274 [cs.HC]

(or arXiv:2608.04274v1 [cs.HC] for this version)

https://doi.org/10.48550/arXiv.2608.04274 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

https://doi.org/10.1145/3830398.3830671 Focus to learn more DOI(s) linking to related resources

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