Information propagation in stochastic networks

Péter L. Juhász

Physica A: Statistical Mechanics and its Applications, 2021, vol. 577, issue C

Abstract: In this paper, a network-based stochastic information propagation model is developed. The information flow is modeled by a probabilistic differential equation system. The numerical solution of these equations leads to the expected number of informed nodes as a function of time and reveals the relationship between the degrees of the nodes and their reception time. The validity of the model is justified by Monte Carlo network simulation through the analysis of information propagation in scale-free and Erdős–Rényi networks. It has been found that the developed model provides more accurate results compared to the widely used network-based SI mean-field model, especially in sparse networks.

Keywords: Information propagation; Complex system; Complex network; Stochastic model; SI model; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:577:y:2021:i:c:s0378437121003435

DOI: 10.1016/j.physa.2021.126070

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