Co-Diffusion of Social Contagions

TL;DR

This paper introduces a new threshold model for the co-diffusion of multiple social contagions on multiplex networks, examining how synergy and dormancy affect spread dynamics through simulations.

Contribution

It proposes a novel model for multiple contagions on multiplex networks, incorporating synergy and dormancy effects, and analyzes their impact via Monte Carlo simulations.

Findings

Lower synergy increases contagion percolation, especially on lattice networks.

Faster diffusion with dormancy can block other contagions, similar to ring vaccination.

Contagions on lattices can exhibit bimodal or trimodal spreading patterns within certain synergy ranges.

Abstract

Prior social contagion models consider the spread of either one contagion at a time on interdependent networks or multiple contagions on single layer networks or under assumptions of competition. We propose a new threshold model for the diffusion of multiple contagions. Individuals are placed on a multiplex network with a periodic lattice and a random-regular-graph layer. On these population structures, we study the interface between two key aspects of the diffusion process: the level of synergy between two contagions, and the rate at which individuals become dormant after adoption. Dormancy is defined as a looser form of immunity that models the ability to spread without resistance. Monte Carlo simulations reveal lower synergy makes contagions more susceptible to percolation, especially those that diffuse on lattices. Faster diffusion of one contagion with dormancy probabilistically blocks the diffusion of the other, in a way similar to ring vaccination. We show that within a band of synergy, contagions on the lattices undergo bimodal or trimodal branching if they are the slower diffusing contagion.