"Splendid Isolation": The reproduction of music industry inequalities in Spotify's recommendation system

被引:24
作者
Tofalvy, Tamas [1 ]
Koltai, Julia [2 ,3 ,4 ]
机构
[1] Budapest Univ Technol & Econ, Budapest, Hungary
[2] Ctr Social Sci, Computat Social Sci Res Ctr Educ & Network Studie, Budapest, Hungary
[3] Eotvos Lorand Univ, Fac Social Sci, Budapest, Hungary
[4] Cent European Univ, Dept Network & Data Sci, Vienna, Austria
关键词
Algorithms; core-periphery; Hungary; inequality; metal music; network analysis; popular music; recommendation systems; Spotify; streaming platforms; ECONOMIC-GEOGRAPHY; DIGITAL MUSIC; METAL MUSIC; NETWORKS; EXPLORATION; CREATIVITY; SCENES; PLACE; CITY; US;
D O I
10.1177/14614448211022161
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
In this article, we argue that offline inequalities, such as core-periphery relations of the music industry, are reproduced by streaming platforms. First, we offer an overview of the reproduction of inequalities and core-periphery dynamics in the music industry. Then we illustrate this through a small-scale network analysis case study of Hungarian metal bands' connections on Spotify. We show that the primary determinant of a given band's international connectedness in Spotify's algorithmic ecosystem is their international label connections. Bands on international labels have more reciprocal international connections and are more likely to be recommended based on actual genre similarity. However, bands signed with local labels or self-published tend to have domestic connections and to be paired with other artists by Spotify's recommendation system according to their country of origin.
引用
收藏
页码:1580 / 1604
页数:25
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