Natural growth model of weighted complex networks

TL;DR

This paper introduces a natural model for evolving weighted networks where new links can connect existing nodes, capturing real-world network features and enabling predictions for networks like airports and collaborations.

Contribution

The paper presents a novel weighted network growth model allowing inner links, providing insights into the power-law distributions of network properties.

Findings

Model predicts power-law distributions for strength, degree, and weight.

Applicable to real-world networks like airports and scientific collaborations.

Enhances understanding of weighted network evolution.

Abstract

We propose a natural model of evolving weighted networks in which new links are not necessarily connected to new nodes. The model allows a newly added link to connect directly two nodes already present in the network. This is plausible in modeling many real-world networks. Such a link is called an inner link, while a link connected to a new node is called an outer link. In view of interrelations between inner and outer links, we investigate power-laws for the strength, degree and weight distributions of weighted complex networks. This model enables us to predict some features of weighted networks such as the worldwide airport network and the scientific collaboration network.