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

Abstract

<jats:p> 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. </jats:p>

Musical preferences of Brazilian high school students

“…For this study, we chose gender and age as predictive variables. According to Anderson et al [ 63 ], musical preferences could be better analyzed when they are combined with measures of habitual listening behaviors, which would predict the listeners’ personalities. Thus, future studies should include variables such as personality and music consumption habits in addition to those used in the present study.…”

Preferred musical attribute dimensions underlie individual differences in music-induced analgesia

“…Another future avenue for research is to understand the role of individual differences in how personality impacts MIA. Research building on interactionist theories 37 has shown that individual differences in musical preferences regarding both broad styles and specific attributes are associated with personality traits and cognition 17 , 38 – 40 . Furthermore, recent research has shown evidence for the self-congruity effect of music, whereby listeners prefer the music of artists who have similar personal characteristics as themselves 41 .…”

Computational Personality Assessment - An Overview and Perspective

“…The ground truth problem can be boiled down to a conceptual question: What is the most representative and unbiased conceptualization of systematic patterns in human feelings, thoughts, and behavior (i.e., personality)? Virtually all of the latest computational approaches to personality assessment rely on self-reported personality trait scores as the ground truth criteria for evaluating the performance of the newly derived assessment models (e.g., Anderson et al, 2020;Azucar et al, 2018;Gladstone et al, 2019;Stachl, Au, et al, 2020). This circumstance is challenging, because it means that computational assessments are also somewhat limited by the methodological biases and issues that are idiosyncratic to questionnaire-based measures -the outcome these models aim to predict (Boyd & Pennebaker, 2017).…”