Eur. Phys. J. B (2016) 89: 272
https://doi.org/10.1140/epjb/e2016-70264-6

Regular Article

Community detection by label propagation with compression of flow

Complexity Science Center, Institute of Particle Physics, Central China Normal University, Wuhan 430079, P.R. China

^a e-mail: jh@mails.ccnu.edu.cn

Received: 30 April 2016
Received in final form: 25 September 2016
Published online: 12 December 2016

Abstract

The label propagation algorithm (LPA) has been proved to be a fast and effective method for detecting communities in large complex networks. However, its performance is subject to the non-stable and trivial solutions of the problem. In this paper, we propose a modified label propagation algorithm LPAf to efficiently detect community structures in networks. Instead of the majority voting rule of the basic LPA, LPAf updates the label of a node by considering the compression of a description of random walks on a network. A multi-step greedy agglomerative strategy is employed to enable LPAf to escape the local optimum. Furthermore, an incomplete update condition is also adopted to speed up the convergence. Experimental results on both synthetic and real-world networks confirm the effectiveness of our algorithm.