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Musical preferences predict personality: evidence from active listening and Facebook likes

Accepted version
Peer-reviewed

Type

Article

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Authors

Nave, Gideon 
Minxha, Juri 
Greenburg, David 
Kosinski, Michal 
Stillwell, DJ 

Abstract

Research over the past decade has shown that various personality traits are communicated through musical preferences. One limitation of that research is external validity, as most studies have assessed individual differences in musical preferences using self-reports of music-genre preferences. Are personality traits communicated through behavioral manifestations of musical preferences? We addressed this question in two large-scale online studies with demographically diverse populations. Study 1 (N = 22,252) shows that reactions to unfamiliar musical excerpts predicted individual differences in personality—most notably, openness and extraversion—above and beyond demographic characteristics. Moreover, these personality traits were differentially associated with particular music-preference dimensions. The results from Study 2 (N = 21,929) replicated and extended these findings by showing that an active measure of naturally occurring behavior, Facebook Likes for musical artists, also predicted individual differences in personality. In general, our findings establish the robustness and external validity of the links between musical preferences and personality.

Description

Keywords

machine learning, music, online behavior, personality, prediction, open data, open materials

Journal Title

Psychological Science

Conference Name

Journal ISSN

0956-7976
1467-9280

Volume Title

29

Publisher

SAGE