Musical Preferences Predict Personality: Evidence From Active Listening and Facebook Likes

Gideon Nave, Juri Minxha, David M. Greenberg, Michal Kosinski, David Stillwell, Jason Rentfrow

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

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.

Original languageEnglish
Pages (from-to)1145-1158
Number of pages14
JournalPsychological Science
Volume29
Issue number7
DOIs
StatePublished - 1 Jul 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2018.

Keywords

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

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