Detecting Community Structure of Complex Networks Based on Network Potential

  • Yuxin Zhao
  • Chenglin Zhao
  • Xiuzhen Chen
  • Shenghong Li
  • Hao Peng
  • Yueguo Zhang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 202)

Abstract

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.

Keywords

Complex network Community structure Network potential 

Notes

Acknowledgments

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).

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Yuxin Zhao
    • 1
  • Chenglin Zhao
    • 2
  • Xiuzhen Chen
    • 1
  • Shenghong Li
    • 1
  • Hao Peng
    • 1
  • Yueguo Zhang
    • 1
  1. 1.Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina

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