Two-stage Community Discovery Algorithm for Directed Dynamic Network Based on Game Theory
A new two-stage community detection algorithm for time series directed networks is presented.In the first stage,the importance of nodes in the network is determined by four matrices:node distance,source node influence,target node influence and node decomposition degree.The second stage determines the core node of the community division according to the importance of the nodes,then makes the core node as the source for cascade dissemination,other nodes determine the degree of follow with each leading node through the game,and finally the community led by the node with the highest degree of follow is selected.An empirical study on the algorithm is carried out in the International trade network show that the algorithm can be applied to the real world time series weighted network.
万方数据
维普
