Social media feed algorithms infer user preferences from their past behaviors. Yet what drives engagement often diverges from what users value. We examine this gap between stated preferences (what users say they prefer) and revealed preferences (what their behavior suggests they prefer) among young adults, a group deeply embedded in algorithmically mediated environments. Using a mixed-methods approach combining surveys and interviews with feed curation activities, we investigate: what gaps exist between stated and revealed preferences; how users make sense of these gaps; what values users believe should guide algorithmic curation; and how systems might reflect those values. Participants often found themselves engaging with low-quality content they did not endorse, despite wanting high-quality information. When asked to curate an ideal social media news feed for a hypothetical persona, participants created feeds they considered more satisfying and higher in quality by prioritizing values such as accuracy and diversity. In doing so, they navigated trade-offs between different values, factoring in social relationships and context surrounding the persona. These findings suggest that feed curation is a socially situated process of judging what should be visible and appropriate in shared information spaces. Based on these insights, we offer design directions for bridging the gap between stated and revealed preferences.

翻译：社交媒体推送算法通过用户过往行为推断其偏好。然而，驱动用户参与的内容往往与用户真正看重的信息存在差异。本研究聚焦深度嵌入算法媒介环境的年轻成人群体，探讨其陈述偏好（用户声称的偏好）与揭示偏好（行为反映的偏好）之间的差距。采用问卷调查与访谈相结合的混合研究方法，结合推送策展活动，我们研究以下问题：陈述偏好与揭示偏好之间存在何种差距；用户如何理解这些差距；用户认为算法策展应遵循哪些价值观；以及系统应如何体现这些价值观。研究发现，参与者常不由自主地消费自己并不认同的低质量内容，即便他们渴望获取高质量信息。当被要求为虚拟人物设计理想的社交媒体新闻推送时，参与者通过优先考虑准确性与多样性等价值观，构建出他们认为更令人满意且质量更高的推送。在此过程中，他们需权衡不同价值观，并将虚拟人物的社会关系与情境因素纳入考量。结果表明，推送策展本质上是一个社会情境化过程，需在信息共享空间中判断内容的可见性与适宜性。基于这些发现，我们提出缩小陈述偏好与揭示偏好之间差距的设计方向。