Year: 2024
Type: article
Abstract: With the rapid development of digital technology and the internet, the music industry is undergoing unprecedented changes. This paper takes Alibaba Music as an example to deeply analyze the key factors affecting music popularity and constructs a prediction model for music trends. Through literature review, the research status and influencing factors of music trends are sorted out. A detailed case study of Alibaba Music's development, user behavior, and recommendation algorithms reveals the impact of user behavior patterns and recommendation algorithms on music popularity. This paper uses time series analysis and machine learning techniques to build a music trend prediction model, which is verified with actual data. The results show that user behavior, recommendation algorithms, and socio-cultural factors are the main factors affecting music popularity, and the prediction model can effectively predict music trends. The paper summarizes the research findings, points out the limitations of the study, and proposes suggestions for the future development of the music industry.
DOI: 10.54691/sftbz407
Authors: Guanyu Ye, Yanxia Zhao, Tian Qiu, Hongyu Wang
Institutions: Zhejiang Yuexiu University, Zhejiang Gongshang University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405765172