Network community detection based on spectral clustering

In recent years, spectral clustering based on the spectral graph theory has become one of the most popular clustering algorithms. It is easy to implement and is widely used in the domain of pattern recognition. In this paper, a new method is proposed to estimate the number of communities based on spectral clustering. The conductivity function and the accuracy are used to evaluate the quality of community detection. Experimental results on Zachary Karate Club show that the proposed method yields a high accuracy and effectiveness.