How to generate a random growing network

TL;DR

This paper introduces a method for constructing a broad class of random evolving networks with fat-tailed degree distributions and customizable clustering, using stochastic transformations of edges, which can serve as a basis for renormalization group analysis.

Contribution

It presents a novel construction procedure for generating complex evolving networks with specific degree and clustering properties.

Findings

Networks with fat-tailed degree distributions successfully generated.

The method allows control over clustering coefficients.

Potential for applying renormalization group techniques to networks.

Abstract

We propose a construction procedure which generates a wide class of random evolving networks with fat-tailed degree distributions and an arbitrary clustering. This procedure applies the stochastic transformations of edges, which can be used as the basis of a real space renormalization group for evolving networks.