Markov-based solution for information diffusion on adaptive social networks

Liu, Chuang; Zhou, Nan; Zhan, Xiu-Xiu; Sun, Gui‐Quan; Zhang, Zi-Ke

doi:10.1016/j.amc.2020.125286

Cited by 39 publications

(16 citation statements)

References 54 publications

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“…The current research related to the transmission of public opinion on social networks mainly focuses on dissemination model [7][8][9] , node preference [10,11] , rumor diffusion [12,13] , network topology [14][15][16] , etc. First, various methods have been proposed to study the dissemination model of network public opinion.…”

Section: Literature Reviewmentioning

confidence: 99%

Public Opinion Dissemination with Incomplete Information on Social Network: A Study Based on the Infectious Diseases Model and Game Theory

Yuan

et al. 2021

Complex Syst. Model. Simul.

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Given the fragmentation of public opinion dissemination and the lag of network users' cognition, the paper analyzes public opinion dissemination with incomplete information, which can provide reference for us to control and guide the spread of public opinion. Based on the derivative and secondary radiation of public opinion dissemination with incomplete information, the Susceptible-Susceptible-Infected-Recovered-Recovered-Infected (SSIR R-I ) model is proposed. Given the interaction between users, the Deffuant opinion dynamics model and evolutionary game theory are introduced to simulate the public opinion game between dissemination and immune nodes. Finally, the numerical simulation and results analysis are given. The results reveal that the rate of opinion convergence significantly affects disseminating public opinion, which is positively correlated with the promotion effect of the dissemination node and negatively correlated with the suppression effect of the immune node of public opinion dissemination. Derivative and secondary radiations have different effects on public opinion dissemination in the early stage, but promote public opinion dissemination in the later stage. The dominant immune nodes have an apparent inhibitory effect on the spread of public opinion; nevertheless, they cannot block the dissemination of public opinion.

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Section: Literature Reviewmentioning

confidence: 99%

Public Opinion Dissemination with Incomplete Information on Social Network: A Study Based on the Infectious Diseases Model and Game Theory

Yuan

et al. 2021

Complex Syst. Model. Simul.

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“…Therefore, this comparative study uses the default SEIR model formulation with varying birth and death rates as well as disease-related deaths as introduced above. Furthermore, there are numerous approaches to studying social impacts over time such as Markov-based solutions for adaptive social networks [32] and time-varying social isolation parameters. However, for the purposes of comparison and given the nature of the recommendations provided to the Canadian population, the simplifying assumption of a constant social distancing impact was assumed in this study.…”

Section: 07234e-5 / Day 42mentioning

confidence: 99%

A Study of the COVID-19 Impacts on the Canadian Population

Yawney

Gadsden

2020

IEEE Access

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With the recent outbreak of COVID-19, the reach and scale of COVID-19 cases is top of mind for everyone and many research groups are actively monitoring and exploring the potential spread. A positive consequence of past epidemics and pandemics is that there are sound epidemiological compartmental modelling approaches that can effectively model disease spread. With minor changes to the underlying dynamical system of equations, many different strategies and situations can be explored. In particular, one such strategy of social distancing is top of mind for many Canadians as our political leaders, local businesses, and fellow Canadians promote and adopt this approach with the hopes that it will effectively 'flatten the curve' and reduce or prevent further spread. In this paper, the baseline model is introduced with its close counterpart, the model. Social distancing is modelled through the isolation of a subset of the susceptible population and comparative studies are performed considering a range in the proportion of individuals isolated. Robust and accurate numerical approximation techniques are used to simulate the pessimistic base case for which no preventative measures are taken and for various social distancing regimes. The results of social distancing are consolidated into two groups-those that flatten the curve and those that completely halt the disease spread. Mathematical formulations show that the turning point between these two regimes is when the effective reproductive rate, denoted , is equal to 1. Conclusions are made regarding the impacts and extent of the spread in relation to the severity of social distancing measures.

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“…Information can be transferred from known individuals to unknown individuals through network interaction. In this process, the interaction between individuals will also change, which will have a significant impact on the dissemination of information [31]. Hence, it is particularly important to establish an effective rumor propagation model and find effective countermeasures to control rumor propagation.…”

Section: Rumor Minimization Mechanism Considering Interlayer Interactionmentioning

confidence: 99%

Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model

et al. 2020

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The widespread of rumors is no doubt harmful to information security and social stability. Therefore, it is necessary to control it effectively. In this paper, a dynamic model with a double-layer interaction process is proposed to explore the impact of network interaction and dynamic evolution. Considering the individual heterogeneity and time-varying, the probability of node state transformation is not a fixed parameter, but closely related to the degree and hyperdegree of each node in the time step . Then, the theoretical analysis is conducted by Microscopic Markov Chain Approach and the impact of each parameter is tested. The simulation results show that the rumor diffusion is not only related to the interaction of the network, but also affected by the dynamic evolution of the network structure. Finally, according to the simulation results, the corresponding control strategies are proposed. The model is universal and can be reduced to traditional double-layer network model or single-layer dynamic hypernetwork model.

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Markov-based solution for information diffusion on adaptive social networks

Cited by 39 publications

References 54 publications

Public Opinion Dissemination with Incomplete Information on Social Network: A Study Based on the Infectious Diseases Model and Game Theory

Public Opinion Dissemination with Incomplete Information on Social Network: A Study Based on the Infectious Diseases Model and Game Theory

A Study of the COVID-19 Impacts on the Canadian Population

Rumor Diffusion and Control Based on Double-Layer Dynamic Evolution Model

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