Burstiness and aging in social temporal networks

TL;DR

This paper introduces an analytically solvable model for social temporal networks that captures burstiness and aging effects, breaking time invariance in degree distribution, validated through simulations and empirical data.

Contribution

It presents a new renewal process-based model that reproduces aging in social networks and provides an analytic solution for their topological properties.

Findings

Model reproduces burstiness and aging effects.

Breaks time translation invariance in degree distribution.

Validated predictions with empirical social network data.

Abstract

The presence of burstiness in temporal social networks, revealed by a power law form of the waiting time distribution of consecutive interactions, is expected to produce aging effects in the corresponding time-integrated network. Here we propose an analytically tractable model, in which interactions among the agents are ruled by a renewal process, and that is able to reproduce this aging behavior. We develop an analytic solution for the topological properties of the integrated network produced by the model, finding that the time translation invariance of the degree distribution is broken. We validate our predictions against numerical simulations, and we check for the presence of aging effects in a empirical temporal network, ruled by bursty social interactions.