Universality of preference behaviors in online music-listener bipartite networks: A Big Data analysis
Xiao-Pu Han, Fen Lin, Jonathan J.H. Zhu, Tarik Hadzibeganovic

TL;DR
This study analyzes the formation and evolution of musical preferences among millions of users on a large Chinese online music platform, revealing universal patterns and cultural differences in preference behaviors.
Contribution
It combines complex network and Big Data analysis to uncover statistical patterns, community structures, and demographic influences on musical preferences in a large-scale online setting.
Findings
Identified eight major cultural communities among users.
Discovered preference variability is higher in females, especially around age 25.
Preferences follow a power-law decay and peak at age 13.
Abstract
We investigate the formation of musical preferences of millions of users of the NetEase Cloud Music (NCM), one of the largest online music platforms in China. We combine the methods from complex networks theory and information sciences within the context of Big Data analysis to unveil statistical patterns and community structures underlying the formation and evolution of musical preference behaviors. Our analyses address the decay patterns of music influence, users' sensitivity to music, age and gender differences, and their relationship to regional economic indicators. Employing community detection in user-music bipartite networks, we identified eight major cultural communities in the population of NCM users. Female users exhibited higher within-group variability in preference behavior than males, with a major transition occurring around the age of 25. Moreveor, the musical tastes and…
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Taxonomy
TopicsMusic History and Culture · Music and Audio Processing · Opinion Dynamics and Social Influence
