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来源类型Working Paper
规范类型报告
DOI10.3386/w29017
来源IDWorking Paper 29017
Playlisting Favorites: Measuring Platform Bias in the Music Industry
Luis Aguiar; Joel Waldfogel; Sarah B. Waldfogel
发表日期2021-07-12
出版年2021
语种英语
摘要Platforms are growing increasingly powerful, raising questions about whether their power might be exercised with bias. While bias is inherently difficult to measure, we identify a context within the music industry that is amenable to bias testing. Our approach requires ex ante platform assessments of commercial promise - such as the rank order in which products are presented - along with information on eventual product success. A platform is biased against a product type if the type attains greater success, conditional on ex ante assessment. Theoretical considerations and voiced industry concerns suggest the possibility of platform biases in favor of major record labels, and industry participants also point to bias against women. Using data on Spotify curators' rank of songs on New Music Friday playlists in 2017, we find that Spotify's New Music Friday rankings favor independent-label music, along with some evidence of bias in favor of music by women. Despite challenges that independent-label artists and women face in the music industry, Spotify's New Music curation appears to favor them.
主题Other ; Law and Economics ; Industrial Organization ; Market Structure and Firm Performance ; Industry Studies
URLhttps://www.nber.org/papers/w29017
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/586691
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Luis Aguiar,Joel Waldfogel,Sarah B. Waldfogel. Playlisting Favorites: Measuring Platform Bias in the Music Industry. 2021.
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