Detecting Community Structure of Complex Networks Based on Network Potential
Community structure is an important topological property of complex networks, which is beneficial to understand the structures and functions of complex networks. In this chapter a new statistical parameter, which we call network potential, is proposed to measure a complex network by introducing the field theories of physics. We then present a detecting algorithm of community structure based on the network potential whose main strategy is partitioning the network by optimizing the value of the network potential. We test our algorithm on both computer-generated networks and real-world networks whose community structure is already known. The experimental results show the algorithm can be effectively utilized for detecting the community structure of complex network.
KeywordsComplex network Community structure Network potential
This work was supported by National Natural Science Foundation of China (61071152), National “Twelfth Five-Year” Plan for Science and Technology Support (2012BAH38B04), and Major State Basic Research Development Program (2010CB731400 and 2010CB731406).
- 20.Liu J, Wang N (2009) Detecting community structure of complex networks by affinity propagation. IEEE Int Conf Intell Comput Intell Syst 4:13–19Google Scholar
- 21.Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anth Res 33(4):452–473Google Scholar