Closure coefficients in scale-free complex networks

Clara Stegehuis*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
52 Downloads (Pure)

Abstract

The formation of triangles in complex networks is an important network property that has received tremendous attention. The formation of triangles is often studied through the clustering coefficient. The closure coefficient or transitivity is another method to measure triadic closure. This statistic measures clustering from the head node of a triangle (instead of from the centre node, as in the often studied clustering coefficient). We perform a first exploratory analysis of the behaviour of the local closure coefficient in two random graph models that create simple networks with power-law degrees: The hidden-variable model and the hyperbolic random graph. We show that the closure coefficient behaves significantly different in these simple random graph models than in the previously studied multigraph models. We also relate the closure coefficient of high-degree vertices to the clustering coefficient and the average nearest neighbour degree.

Original languageEnglish
Article numbercnaa020
JournalJournal of Complex Networks
Volume8
Issue number3
DOIs
Publication statusPublished - 5 Aug 2020

Keywords

  • UT-Hybrid-D
  • Complex networks
  • Random graphs
  • Transitivity
  • Closure coefficient
  • 22/2 OA procedure

Fingerprint

Dive into the research topics of 'Closure coefficients in scale-free complex networks'. Together they form a unique fingerprint.

Cite this