Affective Idiosyncratic Responses to Music

TL;DR

This study develops computational methods to analyze how personal, musical, lyrical, contextual, demographic, and mental health factors influence individual emotional responses to music, based on a large dataset of listener comments.

Contribution

It introduces novel computational techniques to quantify affective responses and systematically examines various factors affecting music-induced emotions and social disclosures.

Findings

Identified key factors influencing emotional responses to music.

Quantified the impact of demographic and mental health variables.

Analyzed social support and self-disclosure patterns among users.

Abstract

Affective responses to music are highly personal. Despite consensus that idiosyncratic factors play a key role in regulating how listeners emotionally respond to music, precisely measuring the marginal effects of these variables has proved challenging. To address this gap, we develop computational methods to measure affective responses to music from over 403M listener comments on a Chinese social music platform. Building on studies from music psychology in systematic and quasi-causal analyses, we test for musical, lyrical, contextual, demographic, and mental health effects that drive listener affective responses. Finally, motivated by the social phenomenon known as w\v{a}ng-y\`i-y\'un, we identify influencing factors of platform user self-disclosures, the social support they receive, and notable differences in discloser user activity.