AI 中文总结
本文研究Bluesky自定义信息流中相同文本的曝光差距，发现新作者相同文本曝光更少，粉丝更多的新作者仍在74%的对比中落败，证明多信息流访问不足以实现相同文本平等曝光。
AI 中文摘要
Bluesky允许用户部署自定义信息流，这些是平台与数千种其他信息流一同提供的独立运行推荐算法。本文研究这些信息流对相同文本帖子的处理均匀程度。为进行测量，我们对1366个公开信息流返回的Top-50列表进行重复快照，将不同作者发布、在同一列表响应前创建且年龄相近的相同文本帖子分组。这些匹配集合分布在250个信息流中，曝光差异巨大：33%的集合中，一个副本出现在列表中而另一个未出现。固定效应回归显示，这种差异与作者在特定信息流上的历史相关：信息流新作者的相同文本曝光更少（倒数排名权重为-0.061），而此前帖子被该信息流返回过的作者则获得更多曝光。即使新作者的粉丝数超过竞争作者，在一对一对比中仍会输掉74%。多重比较校正后，媒体和帖子类型特征未显示可检测的关联。这些结果初步证明，访问众多独立信息流不足以让相同文本获得平等曝光。
英文摘要
Bluesky lets users deploy custom feeds, independently operated recommendation algorithms that the platform serves alongside thousands of others. This paper investigates how evenly these feeds treat posts with the same text. To measure this, we take repeated snapshots of the Top-50 lists that 1,366 public feeds return, and we group posts with identical text, from different authors, that were created before the same list response and closely matched in age. Exposure diverges widely inside these matched sets, which span 250 feeds: in 33% of sets, one copy appears on the list while another does not. Fixed-effects regressions show that this divergence is associated with the author's history on the specific feed. Authors new to a feed receive less exposure for the same text (-0.061 in reciprocal-rank weight), while authors whose posts the feed has returned before receive more. A new author with more followers than the competing author still loses 74\% of head-to-head comparisons. Media and post-type features show no detectable association after multiple-comparison correction. These results are early evidence that access to many independent feeds is not enough to give identical texts equal exposure.
CommentsTo appear at The 20th ACM Recommender Systems Conference (RecSys 2026), please cite accordingly
