A Study of Musical Influence Networks and Genre Evolution Based on the Pagerank Approach

The aim of this study is to investigate the definition of musical influence networks and the construction of multilayer directed networks. By analyzing the provided dataset, the parameters of an artist's musical influence were evaluated and a musical influence network was constructed using the Pagerank method. The study also extends the single-layer network parameters to a multilayer network and proposes a centrality measure based on node degree. In terms of genre analysis, the musical eigenvalues of each genre were calculated using MATLAB software and evaluated by a similarity comparison model and an influence comparison model. The results showed that there was a high degree of similarity between certain genres, and the influence of pop/rock music was the most significant. In addition, the changes and relationships of different genres over time were analyzed through multiple spatio-temporal networks, and the results showed that new musical genres have emerged over time, some of which have similar musical characteristics to existing genres.