Abstract

Is the random walk appropriate for modelling and analysing social processes? We argue that many interesting social phenomena, including epidemics and information diffusion, cannot be modelled as a random walk, but instead must be modelled as broadcast-based or non-conservative diffusion. To produce meaningful results, social network analysis algorithms have to take into account differences between these diffusion processes. We formulate conservative (random walk-based) and non-conservative (broadcast-based) diffusion mathematically and show how these are related to well-known metrics: PageRank and Alpha-Centrality, respectively. This formulation allows us to unify two distinct areas of network analysis–centrality and epidemic models–and leads to insights into the relationship between diffusion and network structure, specifically, the existence of an epidemic threshold in non-conservative …

Metadata

publication

Journal of Complex Networks 12 (1), cnae006, 2024

year

2024

publication date

2024/2/1

authors

Rumi Ghosh, Kristina Lerman, Tawan Surachawala, Konstatin Voevodski, Shanghua Teng

link

https://academic.oup.com/comnet/article-pdf/doi/10.1093/comnet/cnae006/56679610/cnae006.pdf

journal

Journal of Complex Networks

volume

12

issue

1

pages

cnae006

publisher

Oxford University Press