Abstract
Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a ‘multitasking’ behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields.
Highlights
Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena
We focus on the effects of such temporal correlations, both in the dynamics of social interactions and on dynamical processes running on top of a temporal multiplex
We explore the impact of temporal correlations on the dynamics of coupled epidemic/awareness processes unfolding on different layers[25], showing that they can either slow down or speed up the epidemic spread, depending on the region of the parameter space defining the model
Summary
Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena.
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