What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time

Media and Communication

article

Ariadna Matamoros-Fernández¹  Joanne E. Gray¹  Louisa Bartolo¹  Jean Burgess¹  Nicolas Suzor² 

[1] Digital Media Research Centre, Queensland University of Technology, Australia / School of Communication, Queensland University of Technology;Digital Media Research Centre, Queensland University of Technology, Australia / School of Law, Queensland University of Technology

关键词: algorithms;    automation;    content moderation;    digital methods;    platform governance;    YouTube;   

DOI  :  10.17645/mac.v9i4.4184

学科分类：医学（综合）

来源: Cogitatio Press

【 摘 要 】

YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after the one that is currentlyplaying. This feature has been criticized for limiting users’ exposure to a range of diverse media content and informationsources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to addressthese concerns. However, there is little publicly available data to support either the existing concerns or YouTube’s claimsof having addressed them. Drawing on the idea of “platform observability,” this article combines computational and qual‐itative methods to investigate the types of content that the algorithms underpinning YouTube’s “up next” feature amplifyover time, using three keyword search terms associated with sociocultural issues where concerns have been raised aboutYouTube’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 rec‐ommendations associated with the videos. We repeated this exercise for three steps in the recommendation chain andthen examined patterns in the recommended videos (and the channels that uploaded the videos) for each query and theirvariation over time. We found evidence of YouTube’s stated efforts to boost “authoritative” media outlets, but at the sametime, misleading and controversial content continues to be recommended. We also found that while algorithmic recom‐mendations offer diversity in videos over time, there are clear “winners” at the channel level that are given a visibility boostin YouTube’s “up next” feature. However, these impacts are attenuated differently depending on the nature of the issue.

【 授权许可】

CC BY