Affective Idiosyncratic Responses to Music
Sky CH-Wang, Evan Li, Oliver Li, Smaranda Muresan, Zhou Yu
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 网抑云 (wǎng-yì-yún), we identify influencing factors of platform user self-disclosures, the social support they receive, and notable differences in discloser user activity.
BibTeX
@inproceedings{ch-wang-etal-2022-affective,
title = "Affective Idiosyncratic Responses to Music",
author = "CH-Wang, Sky and
Li, Evan and
Li, Oliver and
Muresan, Smaranda and
Yu, Zhou",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.80/",
doi = "10.18653/v1/2022.emnlp-main.80",
pages = "1220--1250"
}