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Cited by 43Recommender Systems and TechniquesMusic History and CultureMusic and Audio Processing

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

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Liu, Meijun, Hu, Xiao, Schedl, Markus·2018·PLOS ONE
DOI 10.1371/journal.pone.0208186PMC PMC6294554
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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.

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Metadata

Authors
Liu, M., Hu, X., & Schedl, M.
Affiliations
  • University of Hong Kong (HK)
  • Johannes Kepler University of Linz (AT)
Corresponding author
Hu, Xiao
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2018-12-14
Volume
13
Issue
12
Pages
e0208186
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0208186
PMC
PMC6294554
OpenAlex
W2904435659
Cited by
43
References
3
Citations by year
2026: 5 · 2025: 8 · 2024: 8 · 2023: 8 · 2022: 6 · 2021: 3 · 2020: 3 · 2019: 2
FWCI
3.09
Type
journal article
Language
en
Update notices
correction (2019-02-13)
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Natural Science Foundation of China (CN) (61703357)
  • Austrian Science Fund (P25655)
Topics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Arts and Humanities › Music › Music History and Culture
  • Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
Keywords
music preference, cross-national differences, cultural dimensions, socioeconomic factors, friendship networks, geographic distance, linguistic distance, music recommendation, music information retrieval, genre preferences
MeSH terms
Choice Behavior, Consumer Behavior, Cross-Cultural Comparison, Female, Humans, Male, Music, Sex Characteristics, Socioeconomic Factors, Friends, Datasets as Topic

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