Mining Direct Antagonistic Communities in Explicit Trust Networks
Conference Proceeding Article
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.
CIKM '11: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, Scotland, 24-28 October 2011
City or Country
Glasgow, United Kingdom
LO, David; Surian, Didi; Kuan, ZHANG; and LIM, Ee Peng.
Mining Direct Antagonistic Communities in Explicit Trust Networks. (2011). CIKM '11: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, Scotland, 24-28 October 2011. 1013-1018. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1398