CLSDJun 16, 2025

Do Music Preferences Reflect Cultural Values? A Cross-National Analysis Using Music Embedding and World Values Survey

arXiv:2506.13199v1h-index: 1
Originality Synthesis-oriented
AI Analysis

It provides insights into cultural boundaries for researchers in musicology and social sciences, though it is incremental in applying existing methods to new data.

This study investigated whether national music preferences reflect cultural values by analyzing popular music data from 62 countries and comparing it to World Values Survey cultural zones, finding significant alignment between music-based clusters and cultural groupings.

This study explores the extent to which national music preferences reflect underlying cultural values. We collected long-term popular music data from YouTube Music Charts across 62 countries, encompassing both Western and non-Western regions, and extracted audio embeddings using the CLAP model. To complement these quantitative representations, we generated semantic captions for each track using LP-MusicCaps and GPT-based summarization. Countries were clustered based on contrastive embeddings that highlight deviations from global musical norms. The resulting clusters were projected into a two-dimensional space via t-SNE for visualization and evaluated against cultural zones defined by the World Values Survey (WVS). Statistical analyses, including MANOVA and chi-squared tests, confirmed that music-based clusters exhibit significant alignment with established cultural groupings. Furthermore, residual analysis revealed consistent patterns of overrepresentation, suggesting non-random associations between specific clusters and cultural zones. These findings indicate that national-level music preferences encode meaningful cultural signals and can serve as a proxy for understanding global cultural boundaries.

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