Online Community Detection for Large Complex Networks

Complex networks describe a wide range of systems in nature and society. To understand the complex networks, it is crucial to investigate their internal structure. In this paper, we propose an online community detection method for large complex networks, which make it possible to process networks edge-by-edge in a serial fashion. We investigate the generative mechanism of complex networks and propose a split mechanism based on the degree of the nodes to create new community. Our method has linear time complexity. The method has been applied to six real-world network datasets and the experimental results show that it is comparable to existing methods in modularity with much less running time.

Authors

• Wangsheng Zhang
• Gang Pan
• Zhaohui Wu
• Shijian Li State Key Laboratory of Brain-machine Intelligence, Zhejiang University； College of Computer Science and Technology, Zhejiang University;

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