Compass：通过原位反思持续对齐社交媒体信息流
Compass: Continuously Aligning Social Media Feeds via In-Situ Reflections
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中文总结 AI 辅助
该研究提出 Compass 系统，通过原位反思与定期模拟行为信号操纵信息流，在 YouTube Shorts 中开展 10 天实地研究，证实其可提升用户反思性消费、偏好调整与信息流对齐效果且不影响浏览随意性。
中文摘要 AI 辅助
社交媒体推荐信息流通常优化用户的即时冲动，而非其经过深度反思后会持有的偏好。部分系统通过配置页面或信息流内控件纳入用户明确偏好，而非仅依赖行为信号，来解决这种错位。但用户偏好会随时间演变，其陈述的偏好与行为自然存在差异，因此需要持续反思与信息流重新对齐。不过现有策略要求用户主动操作，且通常较为费力，实际中很少被调用。我们提出 Compass 系统，通过帮助用户基于自身行为反思并明确偏好，使其信息流与反思后的偏好对齐。为在日常浏览中实现持续反思，Compass 通过轻量通知呈现原位反思，而信息流对齐则通过定期模拟行为信号并直接操纵信息流内容实现。我们将 Compass 嵌入 YouTube Shorts，并开展为期 10 天的实地研究（N=15），将其与无持续支持的基线系统对比。结果发现，Compass 促进了更具反思性和目的性的信息流消费、迭代式偏好调整以及更强的信息流对齐，同时未牺牲信息流浏览的随意性。
英文摘要
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.
发表机构
- The University of Texas at Austin（得克萨斯大学奥斯汀分校）
- University of Washington（华盛顿大学）
机构由 AI 辅助整理，请以论文原文为准。
