Modelling Moral Traits with Music Listening Preferences and Demographics

TL;DR

This study investigates how music listening preferences and demographics can predict individuals' moral values using classification techniques, highlighting music's significant role in moral inference beyond basic demographics.

Contribution

It introduces a novel approach to predict moral traits from music preferences and demographics, demonstrating the predictive power of musical diversity and demographic features.

Findings

Music preferences predict moral values with 0.55-0.69 AUROC.

Demographic features like age and gender improve prediction accuracy.

Music diversity features contribute to understanding moral traits.

Abstract

Music is an essential component in our everyday lives and experiences, as it is a way that we use to express our feelings, emotions and cultures. In this study, we explore the association between music genre preferences, demographics and moral values by exploring self-reported data from an online survey administered in Canada. Participants filled in the moral foundations questionnaire, while they also provided their basic demographic information, and music preferences. Here, we predict the moral values of the participants inferring on their musical preferences employing classification and regression techniques. We also explored the predictive power of features estimated from factor analysis on the music genres, as well as the generalist/specialist (GS) score for revealing the diversity of musical choices for each user. Our results show the importance of music in predicting a person's moral values (.55-.69 AUROC); while knowledge of basic demographic features such as age and gender is enough to increase the performance (.58-.71 AUROC).