A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior
Social and Information Networks
2025-12-04 v2 Information Theory
math.IT
Optimization and Control
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.
Cite
@article{arxiv.2510.22501,
title = {A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior},
author = {Tran Van Khanh and Do Xuan Cho and Hoang Phi Dung},
journal= {arXiv preprint arXiv:2510.22501},
year = {2025}
}