“Just the Way You Are”: Linking Music Listening on Spotify and Personality

Ian Anderson, Santiago Gil, Clay Gibson, Scott Wolf, Will Shapiro, Oguz Semerci, David M. Greenberg

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Advances in digital technology have put music libraries at people’s fingertips, giving them immediate access to more music than ever before. Here we overcome limitations of prior research by leveraging ecologically valid streaming data: 17.6 million songs and over 662,000 hr of music listened to by 5,808 Spotify users spanning a 3-month period. Building on interactionist theories, we investigated the link between personality traits and music listening behavior, described by an extensive set of 211 mood, genre, demographic, and behavioral metrics. Findings from machine learning showed that the Big Five personality traits are predicted by musical preferences and habitual listening behaviors with moderate to high accuracy. Importantly, our work contrasts a recent self-report-based meta-analysis, which suggested that personality traits play only a small role in musical preferences; rather, we show with big data and advanced machine learning methods that personality is indeed important and warrants continued rigorous investigation.

Original languageEnglish
Pages (from-to)561-572
Number of pages12
JournalSocial Psychological and Personality Science
Volume12
Issue number4
DOIs
StatePublished - May 2021

Bibliographical note

Publisher Copyright:
© The Author(s) 2020.

Keywords

  • Big Five personality model
  • computational social science
  • musical preferences
  • personality

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