Title: Label propagation algorithm: a semi-synchronous approach

Authors: Gennaro Cordasco; Luisa Gargano

Addresses: Dipartimento di Psicologia, Second University of Naples, Caserta 81100, Italy. ' Dipartimento di Informatica, University of Salerno, Fisciano 84084, Italy

Abstract: A recently introduced novel community detection strategy is based on a label propagation (LP) algorithm which uses the diffusion of information in the network to identify communities. Studies of LP algorithms showed that the strategy is effective in finding a good community structure. Label propagation step can be performed in parallel on all nodes (synchronous model) or sequentially (asynchronous model); both models present some drawback, e.g., algorithm termination is not granted in the first case, performances can be worst in the second case. In this paper, we present a semi-synchronous version of LP algorithms which aims to combine the advantages of both synchronous and asynchronous models. We prove that our models always converge to a stable labelling. Moreover, we experimentally investigate the effectiveness of the proposed strategy comparing its performance with the asynchronous model both in terms of quality, efficiency and stability. Tests show that the proposed protocol does not harm the quality of the partitioning. Moreover, it is quite efficient; each propagation step is extremely parallelisable and it is more stable than the asynchronous model, thanks to the fact that only a small amount of randomisation is used by our proposal.

Keywords: community discovery; label propagation algorithms; distributed algorithms; graph colouring; community structure; network communities; complex networks.

DOI: 10.1504/IJSNM.2012.045103

International Journal of Social Network Mining, 2012 Vol.1 No.1, pp.3 - 26

Received: 21 Feb 2011
Accepted: 20 Jun 2011

Published online: 21 Aug 2014 *

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