Author(s)

Jiamin Feng ¹

Affiliation(s)

¹ Foshan University, Foshan, Guangdong 528000

Corresponding Author

Jiamin Feng

ABSTRACT

Nowadays, music plays a more and more important role in enriching human spiritual life. In this paper, we establish a model to quantify the influence of music and capture the interaction between music artists based on music feature data. At the same time, we analyze the differences between artists and genres. In order to better understand the evolution and change trend of music development, we use complex networks to analyze the "influence _ data" data set, and establish a multi-directional network of music influence. After that, through the analysis of network association rules, we can get three parameters of music influence, that is, the followers' ability to inherit music, the followers' ability to derive music, and the influence of influencers on music influence. Through the analysis of network association rules. In the end, we can get the inheritance and derivative relationship between schools. These three parameters are the followers' ability to inherit music, the followers' ability to derive the rate of music variation and the influencers' influence on music.

KEYWORDS

Complex network, music influence, Graph theory, Network modeling

CITE THIS PAPER

Jiamin Feng. Network Analysis method of Multi-directional Music influence based on Graph Theory. Art and Performance Letters (2021) 2: 23-26. DOI: http://dx.doi.org/10.23977/artpl.2021.020504.

REFERENCES

[1] Miwa N. The Necessity of Communication through Music in the Growth Process of Human Beings (I) [J]. Journal of the Faculty of Global Communication Siebold University of Nagasaki, 2005, 6: 165-174.
[2] Ma Haiying, Xiao Yuzhi, Zhao Haixing, Wu Huan, Luo Haixiu. Three-layer complex network model construction and characteristic analysis [J]. Complex Systems and Complexity Science, 2020, 17(04): 16-29.
[3] Diestel R. Graph Theory [J]. Mathematical Gazette, 2000, 173(502): 67-128.
[4] Awerbuch B, Shavitt Y. Topology aggregation for directed graph [C] // IEEE Symposium on Computers & Communications. IEEE, 1998.

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