Detecting Community Structure In Complex Networks Based On Modularity Optimization Method

摘要

Discovering community structure in large and complex networks has important practical application value. The discovery means the partition of a network into communities of densely connected nodes, with the nodes belonging to different communities being only sparsely connected. Based on modularity optimization, we proposed a new algorithm to detect community structure in large and complex network. Some experiments on benchmark networks show that our method not only uncovers valid communities but also owns better performance. Finally we give some discussion and future work.