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Musical preference in an online music community in China

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Abstract

Online music communities reflect and influence people’s music tastes, providing a detailed digital record of individuals’ behavior. There have been extensive studies on human musical preference; however, the further questions of how the preferences correlate, how intensive and extensive a musical preference can spread in social networks and an individual’s preference is like his/her neighbors, and which factors are most relevant to the diversity of individual music preference are not well explored. In this paper, we analyze the music preference of users in a large online music community in China. We find that there exists obvious correlated musical preference for certain pairs of genres or languages. The preference locality leads to the decay of preference similarity between users and their neighbors with network distance, and the decay is asymmetric for fans and followees in terms of preference probability, preference distribution similarity and list similarity. Users’ musical preference well reflects their ethnic, cultural, and demographic features. We quantify preference diversity, reveal the factors which are significantly correlated with or can predict the diversity, and find that the mean diversity of users’ nearest fans can be the most important predictor. This study reveals the characteristics of users’ music preference, producing new sights on musical tastes, their diversity determinants, and their correlation with surrounding communities and cultures.

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Acknowledgements

We would like to thank anonymous referees for crucial comments and suggestions that helped us to improve the quality of the paper. The study was partly supported by the National Natural Science Foundation of China (Grant Number: 61973121).

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Correspondence to Haibo Hu.

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The dataset supporting the paper and the supplementary material are available via the following link: https://doi.org/10.6084/m9.figshare.12738224.

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Zhang, J., Hu, H. Musical preference in an online music community in China. Soc. Netw. Anal. Min. 12, 36 (2022). https://doi.org/10.1007/s13278-022-00866-z

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  • DOI: https://doi.org/10.1007/s13278-022-00866-z

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