Clustering in complex directed networks

Giorgio Fagiolo
Phys. Rev. E 76, 026107 – Published 16 August 2007

Abstract

Many empirical networks display an inherent tendency to cluster, i.e., to form circles of connected nodes. This feature is typically measured by the clustering coefficient (CC). The CC, originally introduced for binary, undirected graphs, has been recently generalized to weighted, undirected networks. Here we extend the CC to the case of (binary and weighted) directed networks and we compute its expected value for random graphs. We distinguish between CCs that count all directed triangles in the graph (independently of the direction of their edges) and CCs that only consider particular types of directed triangles (e.g., cycles). The main concepts are illustrated by employing empirical data on world-trade flows.

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  • Received 6 February 2007

DOI:https://doi.org/10.1103/PhysRevE.76.026107

©2007 American Physical Society

Authors & Affiliations

Giorgio Fagiolo*

  • Sant’Anna School of Advanced Studies, Laboratory of Economics and Management, Piazza Martiri della Libertà 33, I-56127 Pisa, Italy

  • *giorgio.fagiolo@sssup.it

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Vol. 76, Iss. 2 — August 2007

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