English

Affective Idiosyncratic Responses to Music

Computation and Language 2022-10-19 v1 Artificial Intelligence Computers and Society Sound Audio and Speech Processing

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.

Keywords

Cite

@article{arxiv.2210.09396,
  title  = {Affective Idiosyncratic Responses to Music},
  author = {Sky CH-Wang and Evan Li and Oliver Li and Smaranda Muresan and Zhou Yu},
  journal= {arXiv preprint arXiv:2210.09396},
  year   = {2022}
}

Comments

EMNLP 2022 Main Conference; see Github https://github.com/skychwang/music-emotions

R2 v1 2026-06-28T03:51:37.218Z