In recent years, with the popularity of handheld Internet equipments like mobile phones, increasing numbers of people\ud are becoming involved in the virtual social network. Because of its large amount of data and complex structure, the\ud network faces new challenges of community mining. A label propagation algorithm with low time complexity and\ud without prior parameters deals easily with a large networks. This study explored a new method of community mining,\ud based on label propagation with two stages. The first stage involved identifying closely linked nodes according to their\ud local adjacency relations that gave rise to a micro-community. The second stage involved expanding and adjusting this\ud community through a label propagation algorithm (LPA) to finally obtain the community structure of the entire social\ud network. This algorithm reduced the number of initial labels and avoided the merging of small communities in general\ud LPAs. Thus, the quality of community discovery was improved, and the linear time complexity of the LPA was\ud maintained
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