Detecting communities using social ties

Document Type

Conference Proceeding

Publication Date

11-1-2010

Abstract

Many internet-based applications such as social networking websites, online viral marketing, and recommendation network based applications, use social network analysis to improve performance in terms of user-specific information dissemination. The notion of community in a social network is a key concept in such analyses and there has been significant work recently in identifying communities within a social network. In this paper, we formally define the notion of strength of a link, which was informally introduced by Granovetter, and present a divisive hierarchical clustering method to divide the nodes of a social network into disjoint communities. We also introduce the notion of clustering coefficient as a measure of the quality of a community or cluster. Our experimental results using some well-known benchmark social networks show that our method determines communities with better clustering coefficient than the well known Girvan-Newman method. © 2010 IEEE.

Publication Source (Journal or Book title)

Proceedings - 2010 IEEE International Conference on Granular Computing, GrC 2010

First Page

55

Last Page

60

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