Communities and Balance in Signed Networks: A Spectral Approach

Advances in Social Networks Analysis and Mining(2012)

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摘要
Discussion based websites like Epinions.com and Slashdot.com allow users to identify both friends and foes. Such networks are called Signed Social Networks and mining communities of like-minded users from these networks has potential value. We extend existing community detection algorithms that work only on unsigned networks to be applicable to signed networks. In particular, we develop a spectral approach augmented with iterative optimization. We use our algorithms to study both communities and structural balance. Our results indicate that modularity based communities are distinct from structurally balanced communities.
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关键词
mining community,like-minded user,spectral approach,potential value,social networks,balanced community,signed network,iterative optimization,structural balance,community detection algorithm,data mining,iterative methods
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