The relation of culture, socio-economics, and friendship to music preferences: A large-scale, cross-country study

Abstract

Music listening is an inherently cultural behavior, which may be shaped by users’ backgrounds and contextual characteristics. Due to geographical, socio-economic, linguistic, and cultural factors as well as friendship networks, users in different countries may have different music preferences. Investigating cultural-socio-economic factors that might be associated with between-country differences in music preferences can facilitate music information retrieval, contribute to the prediction of users’ music preferences, and improve music recommendation in cross-country contexts. However, previous literature provides limited empirical evidence of the relationships between possible cross-country differences on a wide range of socio-economic aspects and those in music preferences. To bridge this research gap, and drawing on a large-scale dataset, LFM-1b, this study examines the possible relationship between cross-country differences in artist, album, and genre listening frequencies as well as the cross-country distance in geographical, socio-economic, linguistic, cultural, and friendship connections using the Quadratic Assignment Procedure. Results indicate: (1) there is no significant relationship between geographical and economic distance on album, artist, and genre preferences’ distance at the country-level; (2) the cross-country distance of three cultural dimensions (masculinity, long-term orientation, and indulgence) is positively associated with both the album and artist preferences distances; (3) the between-country distance in main languages has a positive relationship with the album, artist, and genre preferences distances across countries; (4) the density of friendship connections among countries negatively correlates to the cross-country preference distances in terms of artist and genre. Findings from this study not only expand knowledge of factors related to music preferences at the country level, but also can be integrated into real-world music recommendation systems that consider country-level music preferences.