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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w29017 |
来源ID | Working 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 |
URL | https://www.nber.org/papers/w29017 |
来源智库 | National Bureau of Economic Research (United States) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/586691 |
推荐引用方式 GB/T 7714 | Luis Aguiar,Joel Waldfogel,Sarah B. Waldfogel. Playlisting Favorites: Measuring Platform Bias in the Music Industry. 2021. |
条目包含的文件 | ||||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
w29017.pdf(426KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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