Proceedings of the Workshop on Computation: Theory and Practice (WCTP 2023)

<Previous Article In Volume
Next Article In Volume>

Exploring the Influence of Intrinsic, Extrinsic, and Crowdsourced Features on Song Popularity

Authors
Sandra Angela Berjamin1, *, Angeli Dianne Mata1, Paolo Montecillo1, Rafael Cabredo1
1De La Salle University Manila, Manila, Philippines
*Corresponding author. Email: sandra_angela_berjamin@dlsu.edu.ph
Corresponding Author
Sandra Angela Berjamin
Available Online 29 February 2024.
DOI
10.2991/978-94-6463-388-7_24How to use a DOI?
Keywords
music analysis; intrinsic; extrinsic; structural equation modeling; hedonic consumption constructs
Abstract

Hit songs from popular music artists have been investigated to help uncover the pattern underlying the unique appeal of their tracks. Given this, intrinsic, extrinsic, and crowdsourced features have been identified as some of the necessary information in determining the popularity of a song. Each of these features alone is lacking in reaching the said objective. As a result, the combination of these features was hypothesized to improve the estimation of the performance of a track. Structural equation modeling was done to check the impact of each of the features to the said performance. Then, the comparison of the random forest, support vector machine, and boosting trees techniques to predict the 10th week of streams for each of the songs was done. In conclusion, the extrinsic, and crowdsourced features were discovered to be the most important, and all three modeling techniques used performed similarly to each other.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the Workshop on Computation: Theory and Practice (WCTP 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
29 February 2024
ISBN
978-94-6463-388-7
ISSN
2589-4900
DOI
10.2991/978-94-6463-388-7_24How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sandra Angela Berjamin
AU  - Angeli Dianne Mata
AU  - Paolo Montecillo
AU  - Rafael Cabredo
PY  - 2024
DA  - 2024/02/29
TI  - Exploring the Influence of Intrinsic, Extrinsic, and Crowdsourced Features on Song Popularity
BT  - Proceedings of the Workshop on Computation: Theory and Practice (WCTP 2023)
PB  - Atlantis Press
SP  - 395
EP  - 412
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-388-7_24
DO  - 10.2991/978-94-6463-388-7_24
ID  - Berjamin2024
ER  -