相同内容在不同用户推荐流中曝光差异巨大，新作者吃亏
Whose Posts Get Ranked: Identical-Text Exposure Gaps in Bluesky Custom Feeds
- 通过抓取1366个公开推荐流的前50列表，对比同文本多作者帖子的曝光
- 33%的同文组中仅一个作者的帖子上榜，新作者获曝光率低74%
- 作者历史记录影响曝光，粉丝数无法抵消新作者劣势
Bluesky 允许用户部署独立运营的自定义推荐算法，平台同时提供数千个此类推荐流。本文研究这些推荐流对相同文本内容的处理是否公平。我们对1366个公开推荐流的前50列表进行重复快照，并将同一文本、不同作者、发布时间相近的帖子归为一组。结果显示，在250个这样的组中，33%的组内仅有一个副本出现在列表中。固定效应回归表明，这种曝光差异与作者在特定推荐流中的历史有关：新作者对于相同内容的曝光度降低（倒数排名权重减少0.061），而曾被该流返回过内容的作者则获得更多曝光。即使新作者粉丝数更多，仍会在一对一比较中输掉74%的情况。媒体类型和帖子类型特征在多重比较校正后未显示出显著关联。这表明，尽管存在大量独立推荐流，但相同内容仍难以获得平等曝光。
原文摘要 · Abstract (English)
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.
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