# Clustering Spectrum of scale-free networks

## TL;DR

This paper investigates the clustering spectrum in scale-free networks, revealing a universal pattern of three regimes in the correlation function and explaining its emergence in large networks.

## Contribution

It introduces a universal curve for the clustering spectrum in scale-free networks and analytically explains its properties and dependence on network size.

## Key findings

- The clustering spectrum follows a universal three-regime curve.
- The power-law decay of clustering depends on degree distribution.
- Large networks exhibit the predicted universal curve properties.

## Abstract

Real-world networks often have power-law degrees and scale-free properties such as ultra-small distances and ultra-fast information spreading. In this paper, we study a third universal property: three-point correlations that suppress the creation of triangles and signal the presence of hierarchy. We quantify this property in terms of $\bar c(k)$, the probability that two neighbors of a degree-$k$ node are neighbors themselves. We investigate how the clustering spectrum $k\mapsto\bar c(k)$ scales with $k$ in the hidden variable model and show that $c(k)$ follows a {\it universal curve} that consists of three $k$-ranges where $\bar c(k)$ remains flat, starts declining, and eventually settles on a power law $\bar c(k)\sim k^{-\alpha}$ with $\alpha$ depending on the power law of the degree distribution. We test these results against ten contemporary real-world networks and explain analytically why the universal curve properties only reveal themselves in large networks.