Work

Discovering communities in complex networks by edge label propagation

Year: 2016

Type: article

Abstract: The discovery of the community structure of real-world networks is still an open problem. Many methods have been proposed to shed light on this problem, and most of these have focused on discovering node community. However, link community is also a powerful framework for discovering overlapping communities. Here we present a novel edge label propagation algorithm (ELPA), which combines the natural advantage of link communities with the efficiency of the label propagation algorithm (LPA). ELPA can discover both link communities and node communities. We evaluated ELPA on both synthetic and real-world networks, and compared it with five state-of-the-art methods. The results demonstrate that ELPA performs competitively with other algorithms.

Source: Scientific Reports

DOI: 10.1038/srep22470

Authors: Wei Liu, Xingpeng Jiang, Matteo Pellegrini, Xiaofan Wang

Institutions: Shanghai Jiao Tong University, Central China Normal University, University of California, Los Angeles

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,690

Funders: National Natural Science Foundation of China, Science Fund for Creative Research Groups