Iterative group-based and difference ranking method for online rating systems with spamming attacks

Quan Yun Fu, Jian Feng Ren, Hong Liang Sun

Research output: Journal PublicationArticlepeer-review

3 Citations (Scopus)
3 Downloads (Pure)

Abstract

It is significant to assign reputation scores to users and identify spammers in the bipartite rating networks. In this paper, we propose an Iterative Group-based and Difference Ranking (IGDR) method, which is based on the original Iterative Group-based Ranking (IGR) method. The IGR method considers users grouping behaviors, but it ignores the characteristics of the individual ratings. It is discovered that individual rating characteristics could also contribute to the redistribution of reputation scores of users. The user with a smaller rating deviation will be given a higher reputation score. The proposed method outperforms IGR method ranging from 8% to 163% tested on three real datasets. It also can be applied to deal with big data in a short time.

Original languageEnglish
Article number2150059
JournalInternational Journal of Modern Physics C
Volume32
Issue number05
DOIs
Publication statusPublished - May 2021

Keywords

  • Complex networks
  • rating networks
  • spamming attacks

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy (all)
  • Computer Science Applications
  • Computational Theory and Mathematics

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