Dynamics of Rumor Spreading in Complex Networks

TL;DR

This paper develops a mean-field model for rumor spreading in complex networks, compares analytical, Monte Carlo, and numerical results, and explores different spreading algorithms in scale-free networks for applications in social and technological systems.

Contribution

It introduces a comprehensive mean-field framework for rumor dynamics on heterogeneous networks and analyzes various spreading algorithms through numerical and analytical methods.

Findings

Mean-field equations accurately describe rumor spread in homogeneous networks.

Spreading dynamics vary significantly across different algorithms in scale-free networks.

Numerical methods effectively complement analytical solutions for complex network topologies.

Abstract

We derive the mean-field equations characterizing the dynamics of a rumor process that takes place on top of complex heterogeneous networks. These equations are solved numerically by means of a stochastic approach. First, we present analytical and Monte Carlo calculations for homogeneous networks and compare the results with those obtained by the numerical method. Then, we study the spreading process in detail for random scale-free networks. The time profiles for several quantities are numerically computed, which allow us to distinguish among different variants of rumor spreading algorithms. Our conclusions are directed to possible applications in replicated database maintenance, peer to peer communication networks and social spreading phenomena.