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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.22501 |
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| _version_ | 1866918229515960320 |
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| author | Van Khanh, Tran Cho, Do Xuan Dung, Hoang Phi |
| author_facet | Van Khanh, Tran Cho, Do Xuan Dung, Hoang Phi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_22501 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior Van Khanh, Tran Cho, Do Xuan Dung, Hoang Phi Social and Information Networks Information Theory Optimization and Control 68xx, 68M, 68W H.1.1; G.2.2; G.3 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. |
| title | A Novel Discrete-time Model of Information Diffusion on Social Networks Considering Users Behavior |
| topic | Social and Information Networks Information Theory Optimization and Control 68xx, 68M, 68W H.1.1; G.2.2; G.3 |
| url | https://arxiv.org/abs/2510.22501 |