Integrated structure investigation in complex networks by label propagation

Tao Wu, Yuxiao Guo, Leiting Chen and Yanbing Liu

Physica A: Statistical Mechanics and its Applications, 2016, vol. 448, issue C, 68-80

Abstract: The investigation of network structure has important significance to understand the functions of various complex networks. The communities with hierarchical and overlapping structures and the special nodes like hubs and outliers are all common structure features to the networks. Network structure investigation has attracted considerable research effort recently. However, existing studies have only partially explored the structure features. In this paper, a label propagation based integrated network structure investigation algorithm (LINSIA) is proposed. The main novelty here is that LINSIA can uncover hierarchical and overlapping communities, as well as hubs and outliers. Moreover, LINSIA can provide insight into the label propagation mechanism and propose a parameter-free solution that requires no prior knowledge. In addition, LINSIA can give out a soft-partitioning result and depict the degree of overlapping nodes belonging to each relevant community. The proposed algorithm is validated on various synthetic and real-world networks. Experimental results demonstrate that the algorithm outperforms several state-of-the-art methods.

Keywords: Hierarchical and overlapping community; Hubs and outliers; Label propagation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:448:y:2016:i:c:p:68-80

DOI: 10.1016/j.physa.2015.12.073

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