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Communities and Balance in Signed Networks: A Spectral Approach

机译:签名网络中的社区和平衡:一种光谱方法

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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.
机译:基于epinions.com和slashdot.com等网站允许用户识别朋友和敌人。 这些网络称为签名的社交网络和来自这些网络的志同道合用户的挖掘社区具有潜在价值。 我们扩展了仅在未签名网络上工作的现有社区检测算法,以适用于签名网络。 特别是,我们开发了一种以迭代优化增强的光谱方法。 我们使用算法研究社区和结构平衡。 我们的结果表明,基于模块化的社区与结构平衡的社区不同。

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