Detecting community structure based on edge betweenness

According to the characteristics of edge betweenness in the complex network, if the betweenness of an edge is relative lower, a pair of nodes connected by that edge should be in the same community. An algorithm for detecting community structure is proposed based on this observation. After grouping nodes according to edge betweenness, some nodes not assigned yet to any community in the network are determined by node membership function, which is calculated by the average of weights of nodes in the community connected to that node. If the ratio is higher, the node has more probabilities to be assigned to that community. After all nodes are assigned to corresponding communities, if the number of communities is greater than the predefined number of communities K, the corresponding communities would be merged according to the merging rule until the number of communities is K. The proposed algorithm is tested on the real networks, and it demonstrates the effectiveness and correctness of the algorithm. Furthermore, the algorithm saves the time complexity.

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