The Effects of Communication Burstiness on Consensus Formation and Tipping Points in Social Dynamics

TL;DR

This paper investigates how bursty human communication patterns, characterized by high probabilities of rapid interactions, influence opinion consensus and tipping points in social dynamics, revealing that short-interval activity density significantly impacts group dominance.

Contribution

It demonstrates that burstiness, especially the density of short waiting times, affects opinion competition and consensus formation in social models, extending understanding beyond traditional Poisson assumptions.

Findings

Higher density of short waiting times favors a group's opinion.

Burstiness reduces the fraction of committed individuals needed for consensus.

Early-time burstiness can be quantified by the expected number of rapid activations.

Abstract

Current models for opinion dynamics typically utilize a Poisson process for speaker selection, making the waiting time between events exponentially distributed. Human interaction tends to be bursty, though, having higher probabilities of either extremely short waiting times or long periods of silence. To quantify the burstiness effects on the dynamics of social models, we place in competition two groups exhibiting different speakers' waiting-time distributions. These competitions are implemented in the binary Naming Game, and show that the relevant aspect of the waiting-time distribution is the density of the head rather than that of the tail. We show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the other group. This effect remains in the presence of nodes holding a single opinion that never changes, as the fraction of such committed individuals necessary for achieving consensus decreases dramatically when they have a higher head density than the holders of the competing opinion. Finally, to quantify differences in burstiness, we introduce the expected number of small-time activations and use it to characterize the early-time regime of the system.