Dynamics on networks: competition of temporal and topological correlations

TL;DR

This paper investigates how the interplay between temporal burstiness and topological community structure in dynamic networks influences the speed of processes like spreading, revealing that these correlations can either hinder or accelerate dynamics depending on their interaction.

Contribution

It introduces a framework to analyze the competing effects of temporal and topological correlations on network dynamics, highlighting their complex interplay.

Findings

Topological correlations delay network processes.

Temporal correlations accelerate network processes.

The combined effect depends on the balance of correlations.

Abstract

Links in many real-world networks activate and deactivate in correspondence to the sporadic interactions between the elements of the system. The activation patterns may be irregular or bursty and play an important role on the dynamics of processes taking place in the network. Information or disease spreading in networks are paradigmatic examples of this situation. Besides burstiness, several correlations may appear in the process of link activation: memory effects imply temporal correlations, but also the existence of communities in the network may mediate the activation patterns of internal an external links. Here we study the competition of topological and temporal correlations in link activation and how they affect the dynamics of systems running on the network. Interestingly, both types of correlations by separate have opposite effects: one (topological) delays the dynamics of processes on the network, while the other (temporal) accelerates it. When they occur together, our results show that the direction and intensity of the final outcome depends on the competition in a non trivial way.