Mining direct antagonistic communities in explicit trust networks

David Lo*, Didi Surian, Kuan Zhang, Ee Peng Lim

*Corresponding author for this work

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

19 Citations (Scopus)

Abstract

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging the unique property of direct antagonistic community. We have experimented with synthetic and real data-sets (myGamma and Epinions) to demonstrate the scalability of our proposed solution.

Original languageEnglish
Title of host publicationCIKM'11
Subtitle of host publicationProceedings of the 2011 ACM International Conference on Information and Knowledge Management
EditorsBettina Berendt, Arjen de Vries, Fan Wenfei, Macdonald Craig, Ounis Iadh, Ruthven Ian
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1013-1018
Number of pages6
ISBN (Print)9781450307178
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: 24 Oct 201128 Oct 2011

Other

Other20th ACM Conference on Information and Knowledge Management, CIKM'11
CountryUnited Kingdom
CityGlasgow
Period24/10/1128/10/11

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