Analysis of AI and Music Art Research Hotspots and Trends Based on Citespace—Taking WOS Data as an Example (2016-2025)

DOI

10.2991/978-2-38476-577-5_36How to use a DOI?

Keywords

AI and Music Art; Research Hotspots; Trend Analysis; Cite Space; WOS

Abstract

With the rapid development and iteration of technology, empowering various disciplines through AI has become a major trend. The integration of AI with the field of music and art provides greater productivity for this art form. As an important branch of art studies, the fusion of music and art with AI algorithms can not only promote the spiral development of sub-disciplines (music performance, music education, etc.) but also provide ideas for the diversified development of music and art with other related sister disciplines (literature, sociology, psychology, etc.). However, current analyses of research trends in music and art still have many shortcomings. This study aims to use CiteSpace 6.4 R1 literature visualization analysis software to conduct a visual analysis of music and art literature data from the Web of Science (WOS) from 2016 to 2025, thereby gaining an understanding of the development trends and research hotspots in music and art. Furthermore, it selects current popular research cases in AI and music and art for detailed analysis. The conclusions are as follows: In the keyword clustering analysis, nursing home resident, art therapy, performing art, and Guangdong China became the top four research clusters. In the time trend analysis, the research from 2016 to 2025 experienced a trend from a high point to a gradual slowdown. Furthermore, the case study found that the application of AI combined with music and art presents both opportunities and challenges.

Copyright

© 2026 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.

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TY  - CONF
AU  - Yuxi Liu
PY  - 2026
DA  - 2026/05/15
TI  - Analysis of AI and Music Art Research Hotspots and Trends Based on Citespace—Taking WOS Data as an Example (2016-2025)
BT  - Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
PB  - Atlantis Press
SP  - 351
EP  - 359
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-577-5_36
DO  - 10.2991/978-2-38476-577-5_36
ID  - Liu2026
ER  -