Optimal modularity in complex contagion

TL;DR

This paper investigates how the modular structure of social networks influences complex contagion spreading, identifying an optimal modularity level that maximizes the likelihood of global cascades, with insights into cascade dynamics.

Contribution

It generalizes previous models by considering multiple communities and uniform seed distribution, providing a deeper understanding of optimal modularity effects.

Findings

Optimal modularity predicts the occurrence of global cascades.

Multiple communities and seed distribution impact cascade dynamics.

Insights into the temporal evolution of cascades at optimal modularity.

Abstract

In this chapter, we apply the theoretical framework introduced in the previous chapter to study how the modular structure of the social network affects the spreading of complex contagion. In particular, we focus on the notion of optimal modularity, that predicts the occurrence of global cascades when the network exhibits just the right amount of modularity. Here we generalize the findings by assuming the presence of multiple communities and an uniform distribution of seeds across the network. Finally, we offer some insights into the temporal evolution of cascades in the regime of the optimal modularity.