基于扩散理论的动态社区挖掘

针对动态社区挖掘问题进行分析和研究，基于优先情节和增长定律，根据节点的度数分布，提出以时间为轴动态模拟社会网络的形成演化机制，同时进行社区划分。以Zachary Club和工二s Miscrablcs网络作为实验数据集，对提出的算法进行了实验验证，结果表明，该算法挖掘到的社区都是强连通社区，能够动态、精确地挖掘网络中存在的社区结构，具有较高的实用价值。

Research of Dynamic Community Discovery Based on Diffusion Theory

In terms of the dynamic community discovery problem, this article came up with the idea of basing on the priority complex and thegrouth theorem and according to the nodes degree distribution to construct the time axis to dynamically simulate the social network' s mechanism of formation and evolution, simultaneously divide the community structures. We used Zachary Club and I_es Miscrables as the experiment data to test our algorithm. Experimental results show that, the communities that the algorithm gets are all strong connected communities, it is able to dynamically, accurately discover the community structure with high practical value.