Affective Idiosyncratic Responses to Music
October 17, 2022 Β· Declared Dead Β· π Conference on Empirical Methods in Natural Language Processing
Repo contents: README.md
Authors
Sky CH-Wang, Evan Li, Oliver Li, Smaranda Muresan, Zhou Yu
arXiv ID
2210.09396
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.CY,
cs.SD,
eess.AS
Citations
1
Venue
Conference on Empirical Methods in Natural Language Processing
Repository
https://github.com/skychwang/music-emotions
β 4
Last Checked
1 month ago
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 wΗng-yΓ¬-yΓΊn, we identify influencing factors of platform user self-disclosures, the social support they receive, and notable differences in discloser user activity.
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