复杂网络社团结构划分方法及其应用

Complex network community structure analysis and application

许多实际的复杂网络都具有明显的社团结构,整个网络的功能实现是网络中各社团相互联系作用的结果。文章分别使用Girvan-Newman算法和Newman快速算法对实际的复杂网络进行社团划分。仿真结果显示,使用两种算法对网络进行社团划分时,都能得到清晰的社团结构,使用GN算法得到的社团数目小于使用NF算法得到的社团数目。NF算法的运行速度明显比GN算法的模块度要快。

Many real complex networks have obvious community structure. The implementation of the function of a network is the result of interactions between communities. Girvan-Newman algorithm and Newman-Fast algorithm are used to detect the community structure of real complex networks in this paper. Results show that the obvious partition of community structures are obtained using the two algorithms, and the number of communities using GN algorithm is smaller than that of NF algorithm. FM algorithm runs faster than GN algorithm.