Contact-based Social Contagion in Multiplex Networks

TL;DR

This paper presents a theoretical framework for modeling epidemic-like social contagion in multiplex networks, highlighting the importance of layer-specific contact probabilities and eigenvalues in determining contagion thresholds.

Contribution

It introduces a contact-based spreading model for multiplex networks and demonstrates the limitations of aggregated graph approaches in multiplex contagion analysis.

Findings

The critical contagion point is determined by the layer with the largest eigenvalue.

Aggregating layers can lead to flawed understanding of contagion dynamics.

The framework applies to real multiplex systems.

Abstract

We develop a theoretical framework for the study of epidemic-like social contagion in large scale social systems. We consider the most general setting in which different communication platforms or categories form multiplex networks. Specifically, we propose a contact-based information spreading model, and show that the critical point of the multiplex system associated to the active phase is determined by the layer whose contact probability matrix has the largest eigenvalue. The framework is applied to a number of different situations, including a real multiplex system. Finally, we also show that when the system through which information is disseminating is inherently multiplex, working with the graph that results from the aggregation of the different layers is flawed.