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Empirical analysis of individual popularity and activity on an online music service system

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  • Hu, Hai-Bo
  • Han, Ding-Yi

Abstract

Quantitative understanding of human behaviors supplies basic comprehension of the dynamics of many socio-economic systems. Based on the log data of an online music service system, we investigate the statistical characteristics of individual activity and popularity, and find that the distributions of both of them follow a stretched exponential form which interpolates between exponential and power law distribution. We also study the human dynamics on the online system and find that the distribution of interevent time between two consecutive listenings of music shows the fat tail feature. Besides, with the reduction of user activity the fat tail becomes more and more irregular, indicating different behavior patterns for users with diverse activities. The research results may shed some light on the in-depth understanding of collective behaviors in socio-economic systems.

Suggested Citation

  • Hu, Hai-Bo & Han, Ding-Yi, 2008. "Empirical analysis of individual popularity and activity on an online music service system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5916-5921.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:23:p:5916-5921
    DOI: 10.1016/j.physa.2008.06.018
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    Citations

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    Cited by:

    1. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    2. Yang, Tian & Feng, Xin & Wu, Ye & Wang, Shengfeng & Xiao, Jinghua, 2018. "Human dynamics in repurchase behavior based on comments mining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 563-569.
    3. Pongnumkul, Suchit & Motohashi, Kazuyuki, 2018. "A bipartite fitness model for online music streaming services," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1125-1137.
    4. Li, Zhenpeng & Tang, Xijin & Zhou, Haijun & Yan, Donghui, 2018. "An empirical investigation and theoretic modeling for the collective online visiting behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 969-980.
    5. Yan, Qiang & Yi, Lanli & Wu, Lianren, 2012. "Human dynamic model co-driven by interest and social identity in the MicroBlog community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1540-1545.
    6. Lin, Zhenquan & Meng, Fan, 2018. "Empirical analysis on the runners’ velocity distribution in city marathons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 533-541.

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