Edge Union of Networks on the Same Vertex Set

TL;DR

This paper investigates how combining two different random network models on the same vertices affects the degree distribution and clustering, providing insights into the properties of their union networks.

Contribution

It introduces an analysis of the degree distribution and clustering coefficient of the union of two random networks on the same vertex set, which is a novel exploration.

Findings

Degree distribution of the union networks characterized.

Clustering coefficient behavior analyzed.

Insights into structural properties of combined networks.

Abstract

Random networks generators like Erdoes-Renyi, Watts-Strogatz and Barabasi-Albert models are used as models to study real-world networks. Let G^1(V,E_1) and G^2(V,E_2) be two such networks on the same vertex set V. This paper studies the degree distribution and cluster coefficient of the resultant networks, G(V, E_1 U E_2).