Publication Type

Conference Proceeding Article

Version

submittedVersion

Publication Date

10-2011

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.

Keywords

Direct antagonistic community, Mining maximal bi-cliques, Signed social network

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media

Research Areas

Data Science and Engineering

Publication

CIKM '11: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, Scotland, 24-28 October 2011

First Page

1013

Last Page

1018

ISBN

9781450307178

Identifier

10.1145/2063576.2063722

Publisher

ACM

City or Country

New York

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1145/2063576.2063722

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