Journal article

Evolution properties of online user preference diversity

  • Guo, Qiang Research Center of Complex Systems Science, University of Shanghai for Science and Technology, China
  • Ji, Lei Research Center of Complex Systems Science, University of Shanghai for Science and Technology, China
  • Liu, Jian-Guo Research Center of Complex Systems Science, University of Shanghai for Science and Technology, China - Data Science and Cloud Service Centre, Shanghai University of Finance and Economics, China - Department of Physics, Fribourg University, Switzerland
  • Han, Jingti Data Science and Cloud Service Centre, Shanghai University of Finance and Economics, China
Show more…
    15.02.2017
Published in:
  • Physica A: Statistical Mechanics and its Applications. - 2017, vol. 468, p. 698–713
English 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.
Faculty
Faculté des sciences et de médecine
Department
Département de Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/305420
Statistics

Document views: 8 File downloads:
  • liu_epo.pdf: 1