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Detection of core-periphery structure in networks by 3-tuple motifs
- Source :
- Chaos, 28, 053121, (2018)
- Publication Year :
- 2017
-
Abstract
- Recently, the core-periphery (CP) structure of networks as one type of meso-scale structure has received attention. The CP structure is composed of a dense core and a sparse connected periphery. In this paper, we propose an algorithm to detect the CP structure based on the 3-tuple motif, which is inspired by the idea of motif. In this algorithm, we first define a 3-tuple motif by considering the property of nodes, and then a motif adjacency matrix is formed based on the defined motif, finally, the detection of the CP structure is converted to find a cluster that minimizes the smallest motif conductance. Our algorithm can detect different CP structures: including single or multiple CP structure; and local or global CP structures. Results in the synthetic and the empirical networks indicate that the method is efficient and can apply to large-scale networks. More importantly, our algorithm is parameter free, where the core and periphery are detected without the need for any predefined parameters.<br />Comment: 10 pages, 9 figures, submitted
- Subjects :
- Physics - Physics and Society
Subjects
Details
- Database :
- arXiv
- Journal :
- Chaos, 28, 053121, (2018)
- Publication Type :
- Report
- Accession number :
- edsarx.1705.04062
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1063/1.5023719