用音乐偏好揭示国家文化差异，发现音乐与价值观高度相关。
Do Music Preferences Reflect Cultural Values? A Cross-National Analysis Using Music Embedding and World Values Survey
- 通过音乐嵌入和语义描述分析62国流行音乐特征
- 音乐聚类与世界价值观调查的文化区高度吻合
- 适合研究跨文化比较、数字人文与音乐社会学的学者
本研究探讨了国家层面的音乐偏好在多大程度上反映深层文化价值观。我们收集了来自62个国家（涵盖西方与非西方地区）的长期流行音乐数据，基于YouTube音乐榜单，并使用CLAP模型提取音频嵌入；同时利用LP-MusicCaps和GPT生成每首歌曲的语义描述。基于对比嵌入法识别出偏离全球音乐常态的国家群体，再通过t-SNE降维可视化。结果与世界价值观调查（WVS）定义的文化区域进行比对，经多元方差分析（MANOVA）和卡方检验验证，音乐聚类显著匹配既有文化分区。残差分析显示特定集群在文化区中存在系统性过代表现，表明音乐偏好与文化背景之间存在非随机关联。研究证明，国家级音乐偏好可作为文化信号的有效代理指标，用于理解全球文化边界。
原文摘要 · Abstract (English)
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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