YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after the one that is currently playing. This feature has been criticized for limiting users’ exposure to a range of diverse media content and information sources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to address these concerns. However, there is little publicly available data to support either the existing concerns or YouTube’s claims of having addressed them. Drawing on the idea of “platform observability,” this article combines computational and qualitative methods to investigate the types of content that the algorithms underpinning YouTube’s “up next” feature amplify over time, using three keyword search terms associated with sociocultural issues where concerns have been raised about YouTube’s role: “coronavirus,” “feminism,” and “beauty.” Over six weeks, we collected the videos (and their metadata, including channel IDs) that were highly ranked in the search results for each keyword, as well as the highly ranked recommendations associated with the videos. We repeated this exercise for three steps in the recommendation chain and then examined patterns in the recommended videos (and the channels that uploaded the videos) for each query and their variation over time. We found evidence of YouTube’s stated efforts to boost “authoritative” media outlets, but at the same time, misleading and controversial content continues to be recommended. We also found that while algorithmic recommendations offer diversity in videos over time, there are clear “winners” at the channel level that are given a visibility boost in YouTube’s “up next” feature. However, these impacts are attenuated differently depending on the nature of the issue.

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什么是“下一个”？调查 YouTube 上跨问题和随时间推移的算法建议

YouTube 的“下一个”功能通过算法选择、建议和显示要在当前播放的视频之后观看的视频。该功能因限制用户接触各种不同的媒体内容和信息源而受到批评；同时，YouTube 报告说他们已经实施了各种技术和政策变更来解决这些问题。但是，几乎没有公开可用的数据来支持现有问题或 YouTube 声称已解决这些问题。本文借鉴“平台可观察性”的理念，结合计算和定性方法来研究支持 YouTube 的“下一个”功能的算法随着时间的推移而放大的内容类型，使用三个与社会文化问题相关的关键词搜索词，这些关键词引起了人们对 YouTube 角色的担忧：“冠状病毒”、“女权主义”和“美丽”。在六周的时间里，我们收集了在每个关键字的搜索结果中排名靠前的视频（及其元数据，包括频道 ID），以及与视频相关的排名靠前的推荐。我们在推荐链的三个步骤中重复了这个练习，然后检查了每个查询的推荐视频（以及上传视频的渠道）中的模式及其随时间的变化。我们发现了 YouTube 声称努力提升“权威”媒体的证据，但与此同时，误导性和有争议的内容仍然被推荐。我们还发现，虽然算法推荐随着时间的推移提供了视频的多样性，但在频道级别有明显的“赢家”，它们在 YouTube 的“下一个”功能中得到了提升。但是，根据问题的性质，这些影响会以不同的方式减弱。