Title: Evaluation analysis of music based on directed weighted complex network and statistics

Authors: Xinyan Ma; Xinyu Zhou; Tingting Mo

Addresses: School of Mathematics and Information Science, Guangxi University, Nanning 530004, China ' School of Mathematics and Information Science, Guangxi University, Nanning 530004, China ' School of Mathematics and Information Science, Guangxi University, Nanning 530004, China

Abstract: Music is influential, previously creative music has a certain degree of influence on new music and artists. The influence can be measured by the similarity of musical characteristics. For this feature, a complex network model is established by using knowledge of graph theory, cluster analysis, etc. Based on data mining and analysis, trends of development in artists and genres are examined, and the characteristics and factors of musical influences are explored by using software such as Gephi and SPSS. Through principal component analysis, three principal components were obtained, which were used to analyse the music metrics. And music metrics is studied by applying important correlation theories. The study of this project can help music lovers to further understand different types of music.

Keywords: music genre; popularity; principal component analysis; PCA; Pearson correlation coefficient; PCC; regression analysis; RA.

DOI: 10.1504/IJART.2021.121054

International Journal of Arts and Technology, 2021 Vol.13 No.4, pp.315 - 335

Received: 14 Jul 2021
Accepted: 10 Oct 2021
Published online: 23 Feb 2022 *

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