Abstract
Music serves as a powerful reflection of individual identity, often aligning with deeper psychological traits. Prior research has established correlations between musical preferences and personality, while separate studies have demonstrated that personality is detectable through linguistic analysis. Our study bridges these two research domains by investigating whether individuals’ musical preferences leave traces in their spontaneous language through the lens of the Big Five personality traits (Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism). Using a carefully curated dataset of over 500,000 text samples from nearly 5,000 authors with reliably identified musical preferences, we build advanced models to assess personality characteristics. Our results reveal significant personality differences across fans of five musical genres. We release resources for future research at the intersection of computational linguistics, music psychology and personality analysis.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 4136 |
| State | Published - 2025 |
| Externally published | Yes |
| Event | 2025 Workshops Identity-aware AI and Awareness in Learning Agents, IAAI-ALA 2025 - Bologna, Italy Duration: 28 Oct 2025 → 28 Oct 2025 |
Bibliographical note
Publisher Copyright:© 2025 Copyright for this paper by its authors.
Keywords
- music psychology
- natural language processing
- personality traits
ASJC Scopus subject areas
- General Computer Science
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