Dynamical analysis of two discrete-time rumor propagation models in online social networks

The main aim of this work is to propose and analyze two discrete-time rumor propagation models in online social networks. These models are discrete-time versions of two well-known continuous-time rumor propagation models constructed in recent studies. We perform a rigorous mathematical analysis for global dynamics of the proposed discrete-time models. More specifically, invariant sets, equilibrium points, and their local and global asymptotic stability are established. The obtained results indicate that the discrete-time models can capture essential dynamical properties of the continuous-time models under easily-verified conditions, but they are particularly advantageous in practical applications and real-life situations. Lastly, several illustrative numerical examples supporting the theoretical findings are reported and discussed.

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Publication Details

Journal
Mathematical Foundations of Computing
Published
2024-09-30
DOI
https://doi.org/10.3934/mfc.2024039
Primary Topic
Opinion Dynamics and Social Influence
Type
article
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article

Dynamical analysis of two discrete-time rumor propagation models in online social networks

Manh Tuan Hoang, Ha Hai Truong, Hoai Thu Pham
Mathematical Foundations of Computing
Opinion Dynamics and Social Influence
article

Dynamical analysis of two discrete-time rumor propagation models in online social networks

Manh Tuan Hoang, Ha Hai Truong, Hoai Thu Pham
article en

Abstract

The main aim of this work is to propose and analyze two discrete-time rumor propagation models in online social networks. These models are discrete-time versions of two well-known continuous-time rumor propagation models constructed in recent studies. We perform a rigorous mathematical analysis for global dynamics of the proposed discrete-time models. More specifically, invariant sets, equilibrium points, and their local and global asymptotic stability are established. The obtained results indicate that the discrete-time models can capture essential dynamical properties of the continuous-time models under easily-verified conditions, but they are particularly advantageous in practical applications and real-life situations. Lastly, several illustrative numerical examples supporting the theoretical findings are reported and discussed.

Mathematical Foundations of ComputingVol. 8(5)
FPT University (VN), Thai Nguyen University (VN)
Openalex Percentile: Top 84%
Opinion Dynamics and Social Influence
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