A fast clustering algorithm for mining social network data

Abstract

Many groups with diverse convictions are interacting online. Interactions in online communities help people to engage each other and enhance understanding across groups. Online communities include multiple sub-communities whose members are similar due to social ties, characteristics, or ideas on a topic. In this research, we are interested in understanding the changes in the relative size and activity of these sub-communities, their merging or splitting patterns, and the changes in the perspectives of the members of these sub-communities due to endogenous dynamics inside the community.

This paper has been withdrawn by the author due to a crucial sign error in figures

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