Social media users have repeatedly advocated for control over the currently opaque operations of feed algorithms. Large language models (LLMs) now offer the promise of custom-defined feeds--but users often fail to foresee the gaps and edge cases in how they define their custom feed. We introduce feed elicitation interviews, an interactive method that guides users through identifying these gaps and articulating their preferences to better author custom social media feeds. We deploy this approach in an online study to create custom BlueSky feeds and find that participants significantly prefer the feeds produced from their elicited preferences to those produced by users manually describing their feeds. Through feed elicitation interviews, we advance users' ability to control their social media experience, empowering them to describe and implement their desired feeds.

翻译：社交媒体用户多次呼吁对当前不透明的信息流算法操作进行控制。大型语言模型（LLM）为实现用户自定义信息流带来了希望——但用户往往无法预见他们在定义自定义信息流时存在的疏漏和边界情况。我们引入信息流激发访谈，这是一种互动方法，通过引导用户识别这些疏漏并阐明其偏好，以更好地创作自定义社交媒体信息流。我们在一项在线研究中部署此方法以创建自定义BlueSky信息流，并发现参与者显著更偏好根据其激发出的偏好所产生的信息流，而非用户手动描述其信息流所产生的信息流。通过信息流激发访谈，我们提升了用户控制其社交媒体体验的能力，使其能够描述并实现他们期望的信息流。