Using explosive percolation in analysis of real-world networks

TL;DR

This paper investigates how explosive percolation can be used to analyze real-world networks, revealing that the nature of the percolation transition depends on network structure and that community structures influence cluster formation near critical points.

Contribution

It introduces a variant of explosive percolation for large networks and demonstrates its dependence on network properties and community structures.

Findings

Percolation transition type depends on network structure.

Community structures are linked to cluster formation near critical points.

The method applies to both real-world and model networks.

Abstract

We apply a variant of the explosive percolation procedure to large real-world networks, and show with finite-size scaling that the university class, ordinary or explosive, of the resulting percolation transition depends on the structural properties of the network as well as the number of unoccupied links considered for comparison in our procedure. We observe that in our social networks, the percolation clusters close to the critical point are related to the community structure. This relationship is further highlighted by applying the procedure to model networks with pre-defined communities.