Generating Temporal Contact Graphs Using Random Walkers

Anton David Almasan; Sergey Shvydun; Ingo Scholtes; Piet Van Mieghem

doi:10.1109/TNSE.2025.3537162

Generating Temporal Contact Graphs Using Random Walkers

Anton David Almasan^*, Sergey Shvydun, Ingo Scholtes, Piet Van Mieghem

^*Corresponding author for this work

Network Architectures and Services

Research output: Contribution to journal › Article › Scientific › peer-review

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.

Original language	English
Number of pages	11
Journal	IEEE Transactions on Network Science and Engineering
DOIs	https://doi.org/10.1109/TNSE.2025.3537162
Publication status	E-pub ahead of print - 2025

Keywords

Generative Models
Markov Process
Network Dynamics
Random Walks
Temporal Networks

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10.1109/TNSE.2025.3537162

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title = "Generating Temporal Contact Graphs Using Random Walkers",

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.",

keywords = "Generative Models, Markov Process, Network Dynamics, Random Walks, Temporal Networks",

author = "Almasan, {Anton David} and Sergey Shvydun and Ingo Scholtes and Mieghem, {Piet Van}",

year = "2025",

doi = "10.1109/TNSE.2025.3537162",

language = "English",

journal = "IEEE Transactions on Network Science and Engineering",

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T1 - Generating Temporal Contact Graphs Using Random Walkers

AU - Almasan, Anton David

AU - Shvydun, Sergey

AU - Scholtes, Ingo

AU - Mieghem, Piet Van

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

KW - Generative Models

KW - Markov Process

KW - Network Dynamics

KW - Random Walks

KW - Temporal Networks

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DO - 10.1109/TNSE.2025.3537162

M3 - Article

AN - SCOPUS:85217021055

SN - 2327-4697

JO - IEEE Transactions on Network Science and Engineering

JF - IEEE Transactions on Network Science and Engineering

ER -

Generating Temporal Contact Graphs Using Random Walkers

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Keywords

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