Frontiers in Art Research, 2021, 3(2); doi: 10.25236/FAR.2021.030210.
Yifan Meng1, Pengfei Liu2, Yu Ping2, Bo Liu2, Shuaishuai Huang2
1College of electrical engineering and automation, Henan Polytechnic University, Jiaozuo, Henan 454003, China
2College of Civil Engineering, Henan Polytechnic University, Jiaozuo, Henan 454003, China
For Task Ⅰ, first we use "influence data" for network analysis, and conclude that influencers will have an impact on most followers. Then the weight of each index is obtained by using the grey comprehensive evaluation method, and the "music influence" evaluation model is obtained.Later, first, the data in "full_music_data" is screened; Principal component analysis is used to reduce the dimension and normalize the data; Pearson correlation analysis is used to get the correlation between each two songs. If the correlation degree is greater than 0.9, the two songs are considered to be similar. Taking three fields as the research object, the mapping analysis shows that there are great differences in the degree of internal and external similarity in different fields. For example, compared Country with R&B, the artists of the genres are more similar, and compared Country with Jazz, the artists of the genres are more similar.
Complex Network Analysis, Principal Component Analysis, Pearson Correlation Analysis, Normalization Processing, Gantt Chart, Gephi
Yifan Meng, Pengfei Liu, Yu Ping, Bo Liu, Shuaishuai Huang. Evaluating the Influence and Evolution of Music Based on Complex Network. Frontiers in Art Research (2021) Vol. 3, Issue 2: 51-54. https://doi.org/10.25236/FAR.2021.030210.
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