Journal article

Identifying online user reputation in terms of user preference

  • Dai, Lu Research Center of Complex Systems Science, University of Shanghai for Science and Technology, China
  • Guo, Qiang Research Center of Complex Systems Science, University of Shanghai for Science and Technology, China
  • Liu, Xiao-Lu School of Economics, Fudan University, Shanghai, China
  • Liu, Jian-Guo Data Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, China
  • Zhang, Yi-Cheng Department of Physics, University of Fribourg, Switzerland
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    15.03.2018
Published in:
  • Physica A: Statistical Mechanics and its Applications. - 2018, vol. 494, p. 403–409
English Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users according to their mapped ratings, the online user reputation is calculated based on the corresponding group sizes. Results for MovieLens and Netflix data sets show that the AUC values of the PGR method can reach 0.9842 (0.9493) and 0.9995 (0.9987) for malicious (random) spammers, respectively, outperforming the results generated by the traditional group- based method, which indicates that the online preference plays an important role for measuring user reputation.
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/306585
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