Advanced modularity-specialized label propagation algorithm for detecting communities in networks

被引:155
作者
Liu, X. [1 ]
Murata, T. [1 ]
机构
[1] Tokyo Inst Technol, Meguro Ku, Tokyo 1528552, Japan
关键词
Community detection; Modularity; Network; Graph; Clustering;
D O I
10.1016/j.physa.2009.12.019
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A modularity-specialized label propagation algorithm (LPAm) for detecting network communities was recently proposed. This promising algorithm offers some desirable qualities. However, LPAm favors community divisions where all communities are similar in total degree and thus it is prone to get stuck in poor local maxima in the modularity space. To escape local maxima, we employ a multistep greedy agglomerative algorithm (MSG) that can merge Multiple pairs of communities at a time. Combining LPAm and MSG, we propose an advanced modularity-specialized label propagation algorithm (LPAm+). Experiments show that LPAm+ successfully detects communities with higher modularity values than ever reported in two commonly used real-world networks. Moreover, LPAm+ offers a fair compromise between accuracy and speed. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:1493 / 1500
页数:8
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