Abstract: Many networks of interest in the sciences, including social networks, computer networks, arc found to divide naturally into communities or modules. Community structure can reflect the heterogeneity and modularity of the rcal- world networks. Finding the communities within a network is a powerful tool for understanding the structure and the functioning of the network. We reviewed some most popular methods for detecting community, including GN algorithm, modularity-based methods, dynamic algorithms, and the methods based on statistical inference. We used the standard testing network Zachary to test the abovcmentioned methods, and analysed the time complexity and conclude the ad- vantages and disadvantages of this methods. Finally, prospected of study on community detection methods.

Key words: Complex networks, Community structure, Community detection, Clustering