Generating correlated networks from uncorrelated ones

TL;DR

This paper introduces a transformation method that converts uncorrelated networks into correlated networks, nearly preserving degree distribution while increasing clustering and relating their percolation properties.

Contribution

The paper presents a novel deterministic transformation that generates correlated networks from uncorrelated ones, maintaining degree distribution and enhancing clustering.

Findings

Transformation nearly preserves degree distribution.

Clustering coefficient significantly increases.

Percolation properties of networks are related through the transformation.

Abstract

In this paper we consider a transformation which converts uncorrelated networks to correlated ones(here by correlation we mean that coordination numbers of two neighbors are not independent). We show that this transformation, which converts edges to nodes and connects them according to a deterministic rule, nearly preserves the degree distribution of the network and significantly increases the clustering coefficient. This transformation also enables us to relate percolation properties of the two networks.