Gleeson, JP,Melnik, S,Ward, JA,Porter, MA,Mucha, PJ

2012

January

Physical Review E

Accuracy of mean-field theory for dynamics on real-world networks

Published

()

COMPLEX NETWORKS HETEROGENEOUS NETWORKS EPIDEMICS SPREAD MODELS

85

Mean-field analysis is an important tool for understanding dynamics on complex networks. However, surprisingly little attention has been paid to the question of whether mean-field predictions are accurate, and this is particularly true for real-world networks with clustering and modular structure. In this paper, we compare mean-field predictions to numerical simulation results for dynamical processes running on 21 real-world networks and demonstrate that the accuracy of such theory depends not only on the mean degree of the networks but also on the mean first-neighbor degree. We show that mean-field theory can give (unexpectedly) accurate results for certain dynamics on disassortative real-world networks even when the mean degree is as low as 4.

10.1103/PhysRevE.85.026106