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March 3, 2026Filomat0 citationsOpen Access

Asymptotic distributions of the average clustering coefficient and its variant

MYMingao YuanXZXiaofeng Zhao

Key Points

  • The average clustering coefficient converges in distribution to the standard normal distribution, highlighting its statistical properties.
  • The variance exhibits a phase transition phenomenon, indicating distinct behaviors in network structures.
  • Overall analysis examines both the average clustering coefficient and the sum of weighted triangles within an inhomogeneous random graph framework.
  • Findings suggest that the two summary statistics respond differently to network geometry, underscoring the importance of selecting appropriate metrics.

Abstract

In network data analysis, summary statistics of a network can provide us with meaningful insight into the structure of the network. The average clustering coefficient is one of the most popular and widely used network statistics. In this paper, we investigate the asymptotic distributions of the average clustering coefficient and its variant of an inhomogeneous random graph. We show that the standardized average clustering coefficient converges in distribution to the standard normal distribution. Interestingly, the variance of the average clustering coefficient exhibits a phase transition phenomenon. The sum of weighted triangles is a variant of the average clustering coefficient. It is recently introduced to detect geometry in a network. We also derive the asymptotic distribution of the sum weighted triangles, which does not exhibit a phase transition phenomenon as the average clustering coefficient. This result signifies the difference between the two summary statistics.

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Cite This Study

Yuan et al. (2025) studied this question.

synapsesocial.com/papers/69a75d2dc6e9836116a26c78https://doi.org/10.2298/fil2515297y
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