Analysis and Modeling of the Music Influence and Evolution

Wang, Xinyan; Kang, Yizhou; Zhang, Yixiang; Cheng, Zhichao

doi:10.1109/icbar55169.2021.00040

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…The influence-data data shows more than 5000 music artists who have complicated influence and following relationships [3]. In this model, influence relationships are stored, and in-fluence parameters are determined.…”

Section: Music Artist Influence Network Modelmentioning

confidence: 99%

A study of music revolution based on influence network and similarity test

Jing¹,

Chen²,

Qiu³

2022

EHSS

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This paper develops a method to quantify the evolution of music and understand the role of humans in the evolution of music. First, a directional music influence network was set to show the parameters of "music influence". Then, a sub-network of the direct influencer network was established to obtain influence relationships, and "musical influence" was described and stored in this sub-network. Finally, a music similarity test model is used to compare which is more similar between artists of the same genre and artists of different genres. By comparing the influence and similarity between genres, the difference and connection of genres was got. Analyze whether "influencers" can actually influence their artists and their music through the above-mentioned similarity data. Then analyze the influence of music characteristics. Identify features representing major evolutions in the development of music from the data and get influencers in the network that represent major evolutions; analyze the evolution of a musical genre over time and explain how the genre or artist has changed over time; and illustrate how the model Express the social, political or technological change at the time.

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Section: Music Artist Influence Network Modelmentioning

confidence: 99%