The troll-trust model for ranking in signed networks

Zhaoming Wu, Charu C. Aggarwal, Jimeng Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Signed social networks have become increasingly important in recent years because of the ability to model trust-based relationships in review sites like Slashdot, Epinions, and Wikipedia. As a result, many traditional network mining problems have been re-visited in the context of networks in which signs are associated with the links. Examples of such problems include community detection, link prediction, and low rank approximation. In this paper, we will examine the problem of ranking nodes in signed networks. In particular, we will design a ranking model, which has a clear physical interpretation in terms of the sign of the edges in the network. Specifically, we propose the Troll-Trust model that models the probability of trustworthiness of individual data sources as an interpretation for the underlying ranking values. We will show the advantages of this approach over a variety of baselines.

Original languageEnglish (US)
Title of host publicationWSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages447-456
Number of pages10
ISBN (Electronic)9781450337168
DOIs
StatePublished - Feb 8 2016
Externally publishedYes
Event9th ACM International Conference on Web Search and Data Mining, WSDM 2016 - San Francisco, United States
Duration: Feb 22 2016Feb 25 2016

Publication series

NameWSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining

Other

Other9th ACM International Conference on Web Search and Data Mining, WSDM 2016
CountryUnited States
CitySan Francisco
Period2/22/162/25/16

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Computer Networks and Communications

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