Efficient algorithm based on neighborhood overlap for community identification in complex networks |
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Authors: | Kun Li Xiaofeng Gong Shuguang Guan C-H Lai |
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Affiliation: | a Temasek Laboratories, National University of Singapore, Singaporeb Beijing-Hong Kong-Singapore Joint Center of Nonlinear and Complex systems (Singapore), National University of Singapore, Kent Ridge, 119260, Singaporec Institute of Theoretical Physics, East China Normal University, Shanghai, 200062, PR Chinad Department of Physics, East China Normal University, Shanghai, 200062, PR Chinae Department of Physics, National University of Singapore, Singapore |
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Abstract: | Community structure is an important feature in many real-world networks. Many methods and algorithms for identifying communities have been proposed and have attracted great attention in recent years. In this paper, we present a new approach for discovering the community structure in networks. The novelty is that the algorithm uses the strength of the ties for sorting out nodes into communities. More specifically, we use the principle of weak ties hypothesis to determine to what community the node belongs. The advantages of this method are its simplicity, accuracy, and low computational cost. We demonstrate the effectiveness and efficiency of our algorithm both on real-world networks and on benchmark graphs. We also show that the distribution of link strength can give a general view of the basic structure information of graphs. |
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Keywords: | Complex networks Community identification Weak ties |
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