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.

Large-scale societal dynamics are reflected in human mood and brain

“…We then subtracted the yielded Pearson correlations from the real ones (prior to calculating the medians) and, as expected, the effect sizes only became larger ( Supplement Fig S7 B ). Moreover, a negative association was also identified for a number of sociocultural distances of the UK from 17 countries using data from Liu et al, 2018 43 ( Supplement Fig S7 ). All of the above supported Casti’s hypothesis of stock markets as a useful metric stick for global societal dynamics 1 .…”

“…S12 ) , and, unlike the main results, also disappear after adjusting for other stock market indexes ( Supplement Table S10 , column 4), confirming that the main effect is not driven by a randomly-seeded 1/f noise. Moreover, we demonstrated that the magnitude of the brain-market links (measured as median squared root correlations) is related to economic and sociocultural ties of the UK to other countries 35,43 ( Supplement Fig S6 and S7 ) and that no other global candidate metrics with 1/f properties (UK seismic activity and mortality rates) exhibit an equivalent level of specificity with respect to the investigated variables ( Supplement Fig S9 ).…”

Exploring Brazilian Cultural Identity Through Reading Preferences

“…As the world becomes more connected with the Internet and other technological advances, people are frequently in touch with foreign cultures. Such a multicultural environment is studied by mainly focusing on how cultural differences affect how people interact with new technologies, such as social media [Nascimento et al 2018], online music [Liu et al 2018, Mondelli et al 2018, and e-learning [Zhao et al 2021]. Nonetheless, even a single country may have different cultural aspects within it.…”

“…Having calculated all the cross-state distances, we apply the Quadratic Assignment Procedure (QAP) [Simpson 2001] test to examine whether such measures are significantly associated with the reading preferences. The QAP test is commonly used in social network analysis and achieves high statistical powers when performed on different types of complex networks [Krackardt 1987, Choi et al 2006, Liu et al 2018, Fredrickson and Chen 2019. Moreover, it is a useful tool for analyzing dyadic datasets, i.e., datasets where pairs of entities are analyzed, which is our case.…”

User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues

“…Notably, this evaluation is based on the LFM1b dataset, which is also utilized in the experiments conducted in this study. Furthermore, Liu et al (2018Liu et al ( , 2017 have uncovered similarities between countries based on cultural and socioeconomic aspects on the artist level and on the album level. Pichl et al (2017) clustered users based on their individual musical preferences and their cultural characteristics.…”