Generating Temporal Contact Graphs Using Random Walkers

TL;DR

This paper introduces RWIG, a novel model using random walkers to generate realistic temporal human contact graphs, with analytical solutions for contact probabilities, advancing understanding of human mobility networks.

Contribution

The paper presents RWIG, a new stochastic model for temporal contact graphs, with analytical derivations, offering a realistic alternative to existing network models.

Findings

RWIG produces contact graphs similar to real human mobility networks.

Closed-form solutions for contact probability distributions are derived.

RWIG is comparable to ER and BA models in realism.

Abstract

We study human mobility networks through timeseries of contacts between individuals. Our proposed Random Walkers Induced temporal Graph (RWIG) model generates temporal graph sequences based on independent random walkers that traverse an underlying graph in discrete time steps. Co-location of walkers at a given node and time defines an individual-level contact. RWIG is shown to be a realistic model for temporal human contact graphs, which may place RWIG on a same footing as the Erdos-Renyi (ER) and Barabasi-Albert (BA) models for fixed graphs. Moreover, RWIG is analytically feasible: we derive closed form solutions for the probability distribution of contact graphs.