Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 432, Issue -, Pages 127-139Publisher
ELSEVIER
DOI: 10.1016/j.physa.2015.03.006
Keywords
Complex networks; Community detection; Multi-resolution methods
Categories
Funding
- Scientific Research Fund of Education Department of Hunan Province [14C0126, 11B128, 14C0127, 14C0112, 12C0505, 14B024]
- Hunan Provincial Natural Science Foundation of China [13JJ4045]
- Xiangtan University [10QDZ20]
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Community detection is of considerable importance for analyzing the structure and function of complex networks. Many real-world networks may possess community structures at multiple scales, and recently, various multi-resolution methods were proposed to identify the community structures at different scales. In this paper, we present a type of multi-resolution methods by using the generalized self-loop rescaling strategy. The self-loop rescaling strategy provides one uniform ansatz for the design of multi-resolution community detection methods. Many quality functions for community detection can be unified in the framework of the self-loop rescaling. The resulting multi-resolution quality functions can be optimized directly using the existing modularity-optimization algorithms. Several derived multi-resolution methods are applied to the analysis of community structures in several synthetic and real-world networks. The results show that these methods can find the pre-defined substructures in synthetic networks and real splits observed in real-world networks. Finally, we give a discussion on the methods themselves and their relationship. We hope that the study in the paper can be helpful for the understanding of the multi-resolution methods and provide useful insight into designing new community detection methods. (C) 2015 Elsevier B.V. All rights reserved.
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