Activity driven modeling of time varying networks

TL;DR

This paper introduces an activity driven model for time-varying networks that captures instantaneous dynamics and explains structural features like hubs based on agents' heterogeneous activity levels.

Contribution

It proposes a novel activity driven modeling framework that encodes instantaneous network dynamics and explains structural properties from agent activity heterogeneity.

Findings

The model effectively describes highly dynamical networks.

It explains the emergence of hubs from agent activity heterogeneity.

The framework allows analytical treatment of time-varying networks.

Abstract

Network modeling plays a critical role in identifying statistical regularities and structural principles common to many systems. The large majority of recent modeling approaches are connectivity driven. The structural patterns of the network are at the basis of the mechanisms ruling the network formation. Connectivity driven models necessarily provide a time-aggregated representation that may fail to describe the instantaneous and fluctuating dynamics of many networks. We address this challenge by defining the activity potential, a time invariant function characterizing the agents' interactions and constructing an activity driven model capable of encoding the instantaneous time description of the network dynamics. The model provides an explanation of structural features such as the presence of hubs, which simply originate from the heterogeneous activity of agents. Within this framework, highly dynamical networks can be described analytically, allowing a quantitative discussion of the biases induced by the time-aggregated representations in the analysis of dynamical processes.