Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model

  • Masahiro Kimura
  • Kazumi Saito
  • Kouzou Ohara
  • Hiroshi Motoda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6926)


We address the problem of detecting anti-majority opinionists using the value-weighted mixture voter (VwMV) model. This problem is motivated by the fact that some people have a tendency to disagree with any opinion expressed by the majority. We extend the value-weighted voter model to include this phenomenon with the anti-majoritarian tendency of each node as a new parameter, and learn this parameter as well as the value of each opinion from a sequence of observed opinion data over a social network. We experimentally show that it is possible to learn the anti-majoritarian tendency of each node correctly as well as the opinion values, whereas a naive approach which is based on a simple counting heuristic fails. We also show theoretically that, in a situation where the local opinion share can be approximated by the average opinion share, it is not necessarily the case that the opinion with the highest value prevails and wins when the opinion values are non-uniform, whereas the opinion share prediction problem becomes ill-defined and any opinion can win when the opinion values are uniform. The simulation results support that this holds for typical real world social networks.


Voter Model Opinion Share Naive Approach Multiple Opinion Viral Marketing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Masahiro Kimura
    • 1
  • Kazumi Saito
    • 2
  • Kouzou Ohara
    • 3
  • Hiroshi Motoda
    • 4
  1. 1.Department of Electronics and InformaticsRyukoku UniversityOtsuJapan
  2. 2.School of Administration and InformaticsUniversity of ShizuokaShizuokaJapan
  3. 3.Department of Integrated Information TechnologyAoyama Gakuin UniversityKanagawaJapan
  4. 4.Institute of Scientific and Industrial ResearchOsaka UniversityOsakaJapan

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