Research on Music Influence Based on PPMCC
- 10.2991/assehr.k.220401.050How to use a DOI?
- Network Science; Music; PPMCC
Music is an important part of human society. Artists will be affected in many ways when creating music, such as the influence between artists, politics, culture, and technology.
This article uses network science to model and analyze the influence of music, focusing on analyzing the influence between artists. There are influence and follow-up relationships between artists, and it is appropriate to describe these relationships with directed diagrams. We built a relationship model based on all existing influencers and followers data, built a relationship model subnet centered on influencers, and built a relationship model from the perspective of music genre, and conducted a multi-faceted analysis of music influence. This paper uses network science to model and analyze the influence of music, focusing on the influence between artists. This paper builds a relationship model based on all the existing influencer and follower data, build a relationship model subnet with the influencer as the center, and build a relationship model from the perspective of music genres to analyze the music influence in many aspects. This paper also develops a similarity measure MMS based on Pearson product moment correlation coefficient (PPMCC). With the passage of time, the music genre with the largest number of artists is analyzed, and it is found that some music characteristics of this school will change greatly with the passage of time. That is to say, the characteristics of the genre are not immutable, but if the change exceeds a certain limit, it will be transformed into other genres. This is the process of music development. Finally, combined with some real-world influence, our model is further extended.
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Tianxing Ma AU - Xiaobin Zhou AU - Bowen Li AU - Peirong Wei AU - Renzong Li AU - Shuyao Fang PY - 2022 DA - 2022/04/08 TI - Research on Music Influence Based on PPMCC BT - Proceedings of the 2022 International Conference on Social Sciences and Humanities and Arts (SSHA 2022) PB - Atlantis Press SP - 247 EP - 251 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220401.050 DO - 10.2991/assehr.k.220401.050 ID - Ma2022 ER -