Examining the Relationship Between Songs and Psychological Characteristics

Miran Pyun; Donghun Kim; Chaeyun Lim; Eunbyul Lee; Jihey Kwon; Sangyup Lee

doi:10.1007/978-3-030-60128-7_8

Examining the Relationship Between Songs and Psychological Characteristics

Miran Pyun, Donghun Kim, Chaeyun Lim, Eunbyul Lee, Jihey Kwon, Sangyup Lee

Department of Communication

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Listening to music may serve both as an indicator of the listener’s emotional situation and as an actor on the listener’s emotions. In this study, we explored the relationship between music and listeners’ psychological characteristics. A total of 59 participants’ music playlists were retrieved, and the audio features of each song were extracted via Spotify API. A total of 8,936 songs were analyzed, and 13 different features were extracted. To understand listeners’ psychological characteristics, a survey was conducted. We found that anxiety and stress are closely related to instrumentalness. Also, anxiety is significantly related to liveness and loudness. This study suggests that music playlists can be an indicator of an individual’s psychological characteristics and acknowledges the possibility that music can enhance and reflect the listener’s psychological well-being.

Original language	English
Title of host publication	HCI International 2020 – Late Breaking Papers
Subtitle of host publication	Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings
Editors	Constantine Stephanidis, Don Harris, Wen-Chin Li, Dylan D. Schmorrow, Cali M. Fidopiastis, Panayiotis Zaphiris, Andri Ioannou, Andri Ioannou, Xiaowen Fang, Robert A. Sottilare, Jessica Schwarz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	105-115
Number of pages	11
ISBN (Print)	9783030601270
DOIs	https://doi.org/10.1007/978-3-030-60128-7_8
Publication status	Published - 2020
Event	22nd International Conference on Human-Computer Interaction,HCII 2020 - Copenhagen, Denmark Duration: 2020 Jul 19 → 2020 Jul 24

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12425 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Human-Computer Interaction,HCII 2020
Country/Territory	Denmark
City	Copenhagen
Period	20/7/19 → 20/7/24

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-60128-7_8

Cite this

Pyun, M., Kim, D., Lim, C., Lee, E., Kwon, J., & Lee, S. (2020). Examining the Relationship Between Songs and Psychological Characteristics. In C. Stephanidis, D. Harris, W-C. Li, D. D. Schmorrow, C. M. Fidopiastis, P. Zaphiris, A. Ioannou, A. Ioannou, X. Fang, R. A. Sottilare, & J. Schwarz (Eds.), HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings (pp. 105-115). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12425 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60128-7_8

Pyun, Miran ; Kim, Donghun ; Lim, Chaeyun et al. / Examining the Relationship Between Songs and Psychological Characteristics. HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. editor / Constantine Stephanidis ; Don Harris ; Wen-Chin Li ; Dylan D. Schmorrow ; Cali M. Fidopiastis ; Panayiotis Zaphiris ; Andri Ioannou ; Andri Ioannou ; Xiaowen Fang ; Robert A. Sottilare ; Jessica Schwarz. Springer Science and Business Media Deutschland GmbH, 2020. pp. 105-115 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{2622ea0845b0416e9750848f61d8b498,

title = "Examining the Relationship Between Songs and Psychological Characteristics",

abstract = "Listening to music may serve both as an indicator of the listener{\textquoteright}s emotional situation and as an actor on the listener{\textquoteright}s emotions. In this study, we explored the relationship between music and listeners{\textquoteright} psychological characteristics. A total of 59 participants{\textquoteright} music playlists were retrieved, and the audio features of each song were extracted via Spotify API. A total of 8,936 songs were analyzed, and 13 different features were extracted. To understand listeners{\textquoteright} psychological characteristics, a survey was conducted. We found that anxiety and stress are closely related to instrumentalness. Also, anxiety is significantly related to liveness and loudness. This study suggests that music playlists can be an indicator of an individual{\textquoteright}s psychological characteristics and acknowledges the possibility that music can enhance and reflect the listener{\textquoteright}s psychological well-being.",

author = "Miran Pyun and Donghun Kim and Chaeyun Lim and Eunbyul Lee and Jihey Kwon and Sangyup Lee",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 22nd International Conference on Human-Computer Interaction,HCII 2020 ; Conference date: 19-07-2020 Through 24-07-2020",

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doi = "10.1007/978-3-030-60128-7_8",

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editor = "Constantine Stephanidis and Don Harris and Wen-Chin Li and Schmorrow, {Dylan D.} and Fidopiastis, {Cali M.} and Panayiotis Zaphiris and Andri Ioannou and Andri Ioannou and Xiaowen Fang and Sottilare, {Robert A.} and Jessica Schwarz",

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Pyun, M, Kim, D, Lim, C, Lee, E, Kwon, J & Lee, S 2020, Examining the Relationship Between Songs and Psychological Characteristics. in C Stephanidis, D Harris, W-C Li, DD Schmorrow, CM Fidopiastis, P Zaphiris, A Ioannou, A Ioannou, X Fang, RA Sottilare & J Schwarz (eds), HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12425 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 105-115, 22nd International Conference on Human-Computer Interaction,HCII 2020, Copenhagen, Denmark, 20/7/19. https://doi.org/10.1007/978-3-030-60128-7_8

Examining the Relationship Between Songs and Psychological Characteristics. / Pyun, Miran; Kim, Donghun; Lim, Chaeyun et al.

HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. ed. / Constantine Stephanidis; Don Harris; Wen-Chin Li; Dylan D. Schmorrow; Cali M. Fidopiastis; Panayiotis Zaphiris; Andri Ioannou; Andri Ioannou; Xiaowen Fang; Robert A. Sottilare; Jessica Schwarz. Springer Science and Business Media Deutschland GmbH, 2020. p. 105-115 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12425 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Examining the Relationship Between Songs and Psychological Characteristics

AU - Pyun, Miran

AU - Kim, Donghun

AU - Lim, Chaeyun

AU - Lee, Eunbyul

AU - Kwon, Jihey

AU - Lee, Sangyup

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N2 - Listening to music may serve both as an indicator of the listener’s emotional situation and as an actor on the listener’s emotions. In this study, we explored the relationship between music and listeners’ psychological characteristics. A total of 59 participants’ music playlists were retrieved, and the audio features of each song were extracted via Spotify API. A total of 8,936 songs were analyzed, and 13 different features were extracted. To understand listeners’ psychological characteristics, a survey was conducted. We found that anxiety and stress are closely related to instrumentalness. Also, anxiety is significantly related to liveness and loudness. This study suggests that music playlists can be an indicator of an individual’s psychological characteristics and acknowledges the possibility that music can enhance and reflect the listener’s psychological well-being.

AB - Listening to music may serve both as an indicator of the listener’s emotional situation and as an actor on the listener’s emotions. In this study, we explored the relationship between music and listeners’ psychological characteristics. A total of 59 participants’ music playlists were retrieved, and the audio features of each song were extracted via Spotify API. A total of 8,936 songs were analyzed, and 13 different features were extracted. To understand listeners’ psychological characteristics, a survey was conducted. We found that anxiety and stress are closely related to instrumentalness. Also, anxiety is significantly related to liveness and loudness. This study suggests that music playlists can be an indicator of an individual’s psychological characteristics and acknowledges the possibility that music can enhance and reflect the listener’s psychological well-being.

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SN - 9783030601270

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - HCI International 2020 – Late Breaking Papers

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A2 - Zaphiris, Panayiotis

A2 - Ioannou, Andri

A2 - Fang, Xiaowen

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PB - Springer Science and Business Media Deutschland GmbH

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Pyun M, Kim D, Lim C, Lee E, Kwon J, Lee S. Examining the Relationship Between Songs and Psychological Characteristics. In Stephanidis C, Harris D, Li W-C, Schmorrow DD, Fidopiastis CM, Zaphiris P, Ioannou A, Ioannou A, Fang X, Sottilare RA, Schwarz J, editors, HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 105-115. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-60128-7_8

Examining the Relationship Between Songs and Psychological Characteristics

Abstract

Publication series

Conference

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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