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Study and Development of a Model for Measuring the Impact of Music

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DOI: 10.23977/artpl.2021.23019 | Downloads: 4 | Views: 876

Author(s)

Ling Kang 1, Huimeng Zheng 2

Affiliation(s)

1 Chang’an university School of civil engineering, Xi'an, Shaanxi, 710018
2 School of Economics and Management, China University of Petroleum (East China), Qingdao, Shandong, 266500

Corresponding Author

Ling Kang

ABSTRACT

In this paper, we use graph theory, probability theory and data mining methods to develop a model to measure the impact of music. Firstly, the influence indexes of 181 influencers are established, and combined with the graph theory knowledge, the score ratio of two artists is used as the network weights to establish the directed graphs corresponding to the artists' music influence. Secondly, to analyze the indicators of music influence change, we first assume the attributes of music as indicators, using the entropy weighting method to determine the weights of ten features, ten years as an interval, weighted and obtained the influence score, and then through polynomial fitting to reach the indicators related to influence change, namely loudness, explicit, follower_num formula.

KEYWORDS

Graph Theory, Pearson correlation coefficient, Entropy weight fitting model

CITE THIS PAPER

Ling Kang, Huimeng Zheng. Study and Development of a Model for Measuring the Impact of Music. Art and Performance Letters (2021) 2: 95-99. DOI: http://dx.doi.org/10.23977/artpl.2021.23019

REFERENCES

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[4] Hu Yuehua,Yu Shicheng,Qi Xiao,Zheng Wenjing,Wang Qiqi,Mao Hongyan. Multiple linear regression model and its application [J]. Chinese Journal of Preventive Medicine, 2019(06): 653-656.
[5] Li Xuerui, Hou Xinggang, Yang Mei. A decision model for industrial design plan preference and its application based on multilevel gray comprehensive evaluation method [J/OL]. JournalofGraphology:1-16[2021-02-09].http://kns-cnki-net.vpn.chd.edu.cn:8080/kcms/detail/10.1034.t.20201222.1410.002.html.

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