Affective Idiosyncratic Responses to Music

October 17, 2022 Β· Declared Dead Β· πŸ› Conference on Empirical Methods in Natural Language Processing

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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 ⭐ 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 wǎng-yì-yún, 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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