A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior

Tran Van Khanh; Do Xuan Cho; Hoang Phi Dung

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arXiv · 2510.22501

A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior

Tran Van Khanh·Do Xuan Cho·Hoang Phi Dung

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Abstract

In this paper, we introduce the SDIR (Susceptible-Delayable-Infected-Recovered) model, an extension of the classical SIR epidemic framework, to provide a more explicit characterization of user behavior in online social networks. The newly merged state D (delayable) represents users who have received the information but delayed its spreading and may eventually choose not to share it at all. Based on the mean-field approximation method, we derive the dynamical equations of the model and investigate its convergence and stability conditions. Under these conditions, we further propose an approximation algorithm for the edge-deletion problem, aiming to minimize the influence of information diffusion by identifying approximate solutions.

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Tran Van Khanh, Do Xuan Cho, Hoang Phi Dung. 2025-10-26. A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior. https://arxiv.org/abs/2510.22501

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