Exploring triad-rich substructures by graph-theoretic characterizations in complex networks

Songwei Jia, Lin Gao, Yong Gao, James Nastos, Xiao Wen, Xindong Zhang and Haiyang Wang

Physica A: Statistical Mechanics and its Applications, 2017, vol. 468, issue C, 53-69

Abstract: One of the most important problems in complex networks is how to detect communities accurately. The main challenge lies in the fact that traditional definition about communities does not always capture the intrinsic features of communities. Motivated by the observation that communities in PPI networks tend to consist of an abundance of interacting triad motifs, we define a 2-club substructure with diameter 2 possessing triad-rich property to describe a community. Based on the triad-rich substructure, we design a DIVision Algorithm using our proposed edge Niche Centrality DIVANC to detect communities effectively in complex networks. We also extend DIVANC to detect overlapping communities by proposing a simple 2-hop overlapping strategy. To verify the effectiveness of triad-rich substructures, we compare DIVANC with existing algorithms on PPI networks, LFR synthetic networks and football networks. The experimental results show that DIVANC outperforms most other algorithms significantly and, in particular, can detect sparse communities.

Keywords: Complex networks; Community detection; Triad-rich substructure; Graph-theoretic characterizations; Edge niche centrality; Overlapping (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437116307087
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:468:y:2017:i:c:p:53-69

DOI: 10.1016/j.physa.2016.10.021

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().