A Center-Based Community Detection Method in Weighted Networks

The study of community detection has received more and more attention in recent years, the problem is very difficult and of great importance in many fields such as sociology, biology and computer science. But most of the algorithms proposed so far could not utilize the weight information within weighted networks, and many of them are so time-consuming that they are not fit for the large-scale networks. We propose a new center-based method, which is especially designed for weighted networks. And the method is also suitable for large-scale network because of its low computational complexity. We demonstrate our method on a synthetic network and two real-world networks. The result shows the high efficiency and precision of our method.