Closure coefficients in scale-free complex networks

    Research output: Working paperProfessional

    45 Downloads (Pure)


    The formation of triangles in complex networks is an important network property that has received tremendous attention. Recently, a new method to measure triadic closure was introduced: the closure coefficient. This statistic measures clustering from the head node of a triangle (instead of from the center node, as in the often studied clustering coefficient). We analyze the behavior 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 multigraph models where its behavior was studied before. We also show that the closure coefficient can be related to the clustering coefficient and the average nearest neighbor degree.
    Original languageEnglish
    Publication statusPublished - 26 Nov 2019

    Publication series
    PublisherCornell University


    • physics.soc-ph
    • cs.SI
    • math.PR


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

    Cite this