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Evolution properties of online user preference diversity

Author

Listed:
  • Guo, Qiang
  • Ji, Lei
  • Liu, Jian-Guo
  • Han, Jingti

Abstract

Detecting the evolution properties of online user preference diversity is of significance for deeply understanding online collective behaviors. In this paper, we empirically explore the evolution patterns of online user rating preference, where the preference diversity is measured by the variation coefficient of the user rating sequence. The statistical results for four real systems show that, for movies and reviews, the user rating preference would become diverse and then get centralized finally. By introducing the empirical variation coefficient, we present a Markov model, which could regenerate the evolution properties of two online systems regarding to the stable variation coefficients. In addition, we investigate the evolution of the correlation between the user ratings and the object qualities, and find that the correlation would keep increasing as the user degree increases. This work could be helpful for understanding the anchoring bias and memory effects of the online user collective behaviors.

Suggested Citation

  • Guo, Qiang & Ji, Lei & Liu, Jian-Guo & Han, Jingti, 2017. "Evolution properties of online user preference diversity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 698-713.
    • Handle: RePEc:eee:phsmap:v:468:y:2017:i:c:p:698-713
    DOI: 10.1016/j.physa.2016.10.050
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    References listed on IDEAS

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    Cited by:

    1. Alin ZAMFIROIU & Cristian CIUREA, 2017. "A Model for Users' Profile Recognition based on their Behavior in Online Applications," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(2), pages 181-194.
    2. Li, Ren-De & Liu, Jian-Guo & Guo, Qiang & Zhang, Yi-Cheng, 2018. "Social signature identification of dynamical social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 213-222.
    3. Zhang, Yuhan & Feng, Xin & Wu, Ye & Xiao, Jinghua, 2018. "The dynamics of online ratings with heterogeneous preferences in online review platform," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 26-30.
    4. Wu, Ying-Ying & Guo, Qiang & Liu, Jian-Guo & Zhang, Yi-Cheng, 2018. "Effect of the initial configuration for user–object reputation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 288-294.

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