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

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.

Music Preferences and Personality in Brazilians

“…Thus, for example, the recent study by Nave et al (2018) indicates that an active measure of naturally occurring behavior (i.e., Facebook Likes for musical artists) predicted individual differences in personality.…”

Can Psychological Traits Be Inferred From Spending? Evidence From Transaction Data

“…This means that as personality predictions become more accurate and ubiquitous, and as behavior is recorded digitally at an increasing scale, there is an urgent need for policymakers to ensure that individuals (and societies) are protected against potential abuse of such technologies. Bars represent correlations accounting for attenuation, which we calculated using the alphas reported in the following studies: Facebook Likes (Youyou, Kosinski, & Stillwell, 2014), Facebook status updates (Park et al, 2014), spending records (this study), Flickr pictures (Segalin, Perina, Cristani, & Vinciarelli, 2017), and music preferences (Nave et al, 2018). Alphas were either reported in the original manuscripts or provided by the authors.…”

Promises and perils of experimentation: The mutual internal validity problem

“…Psychology can also incorporate advancements in computer science. For example, researchers have combined big data with machine learning techniques to predict personality (Big-Five traits) from music preferences, Facebook likes, and language use on social media (Greenberg et al, 2016;Kosinski, Bachrach, Kohli, Stillwell, & Graepel, 2014;Nave et al, 2018;Park et al, 2015). These approaches have also been used to map not only geographic variation in personality traits across the United States (Rentfrow, Gosling, & Potter, 2008), but also various political, economic, social, and health outcomes (Rentfrow et al, 2013).…”