Weighted evolving networks: coupling topology and weights dynamics

TL;DR

This paper introduces a model for weighted network growth that integrates topology and weight dynamics, reproducing key properties of real-world networks such as scale-free distributions and evolving vertex characteristics.

Contribution

It presents a novel weight-driven model coupling network topology growth with weight evolution, capturing complex dynamics observed in real systems.

Findings

Networks exhibit scale-free degree, strength, and weight distributions.

Vertex properties evolve non-trivially over time.

Model reproduces statistical features of real-world weighted networks.

Abstract

We propose a model for the growth of weighted networks that couples the establishment of new edges and vertices and the weights' dynamical evolution. The model is based on a simple weight-driven dynamics and generates networks exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a non-trivial time evolution of vertices' properties and scale-free behavior for the weight, strength and degree distributions.