An Innovated SIRS Model for Information Spreading

Shaji, Albin; Belfin, R. V.; Kanaga, E. Grace Mary

doi:10.1007/978-981-10-7200-0_37

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…Specifically, a recovered individual can turn to be susceptible again spontaneously since the company will naturally regard her as a member of the target market. Apart from viral marketing, SIRS model has been applied to various information diffusion processes [17]. For example, among all the epidemic models, SIRS model provides the best interpretation of Internet meme (a phenomenon of contents or concepts that spread rapidly online) activity data [18].…”

Section: A Justification For Using Sirs Modelmentioning

confidence: 99%

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

Liu

Buss

2020

IEEE Trans. Control Netw. Syst.

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In this paper, we investigate the optimal control problems of heterogeneous node-based information epidemics. A node-based Susceptible-Infected-Recovered-Susceptible (SIRS) model is introduced to describe the information diffusion processes taking into account heterogeneities in both network structures and individual characters. Aiming at guiding information dissemination processes towards the desired performance, we propose an optimal control framework with respect to two typical scenarios, i.e., impeding the spread of rumors and enhancing the spread of marketing or campaigning information. We prove the existence of the solutions and solve the optimal control problems by Pontryagin Maximum Principle and forward-backward sweep method. Moreover, numerical experiments validate the using of the node-based SIRS model by comparing with the exact 3 N-state Markov chain model. The effectiveness of the proposed control rules are demonstrated on both models. Further discussion on the influence of the parameters provides insights into the strategies of guiding information diffusion processes.

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Section: A Justification For Using Sirs Modelmentioning

confidence: 99%

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

Liu

Buss

2020

IEEE Trans. Control Netw. Syst.

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“…Based on the traditional SIRS model, Wang et al proposed the SPIRS model with potential propagation nodes and applied it to different real networks, thus indicating that the number of potential nodes can predict the peak of information propagation [8]. After the introduction of the time-varying rate of immune loss in the SIRS model, Shaji et al proposed a new SIRS model and conducted simulation verification on an artificial network [9]. Zhao et al proposed the SIHR social network information transmission model and added hibernation nodes to the model to study the mechanism of forgetting and memory associated with the process of information transmission.…”

Section: Introductionmentioning

confidence: 99%

Analysis of information propagation and control of a layered SITR model in complex networks

Pan

Zhang²

2022

Front. Phys.

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In the field of complex network research, complex network information transmission models based on infectious disease models are often used to study the mechanism of information transmission. This is helpful for the prediction of information transmission trends and the formulation of control strategies. However, the classification of node types in traditional information transmission models is too simple and cannot reflect the characteristics of each node. To solve the above problems, this study proposes a layered SITR complex network information transmission model. The model is layered according to the influence of nodes, and rational propagator nodes are added to optimize it. The propagation threshold of the model is deduced theoretically and the stability of the model is proved. To reduce the dissemination scale of the network’s public opinion information, an optimal control strategy is proposed based on the Pontryagin maximum principle to optimize the information dissemination process. Finally, combined with real events from social network platform, the simulation results show that the layered SITR model can describe the process of network information dissemination more accurately, and the optimal control strategy can effectively reduce the dissemination scale of the network’s public opinion information.

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Identification of best social media influencers using ICIRS model

Devi

Tripathi

2023

Computing

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An Innovated SIRS Model for Information Spreading

Cited by 6 publications

References 12 publications

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

Optimal Control for Heterogeneous Node-Based Information Epidemics Over Social Networks

Analysis of information propagation and control of a layered SITR model in complex networks

Identification of best social media influencers using ICIRS model

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