Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 38, 24 June 2024
Open
Access | Article
Research on popularity of American pop singers’ songs based on machine learning
* Author to whom correspondence should be addressed.
Abstract
The U.S. market of music is the largest market in the globe with its huge influence spreading around, which enables it to be the dominant of the world music industry. The article is produced due to the prevailing music market in U.S. that has phenomenally influence around the world. Therefore, this article takes Taylor Swift as an example thanks to the significant influence power to calculate whether some factors such as acousticness that might directly affect the popularity of singer’s songs for the purpose of formulating some market strategies by corresponding suggestions and advice. The research methods include 3 common mathematical model: linear regression, decision tree and random forest, which indicates that the year of release has the most contribution to the prediction with the value of importance of 0.549929. However other factors seem to have less relativity given the small values for the following 2 factors folklore and reputation with values of importance both below 0.2.
Keywords
Popular songs, linear regression, machine learning
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Mathematical Physics and Computational Simulation
- ISBN (Print)
- 978-1-83558-461-3
- ISBN (Online)
- 978-1-83558-462-0
- Published Date
- 24 June 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/38/20240602
- Copyright
- 24 June 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited