Rumor is an unauthenticated statement that gives significant changes in the social life of the people, financial markets (stocks and trades), etc. By incorporating the dissemination of rumor through groups in social, mobile networks and by considering the people’s cognitive factor (hesitate and forget), a new model on the rumor spreading process is presented in this paper. The spreading dynamics of rumor in homogeneous and heterogeneous networks is analyzed by using mean-field theory. The reproduction number is obtained by using the next-generation matrix. The global stability of the rumor-free equilibrium for the homogeneous and heterogeneous model is proved elaborately. An optimal control problem is developed to minimize the hesitators and infected persons and the existence of optimality is shown using Pontryagin’s Minimum Principle. The hesitating and forgetting mechanism has a great impact on the model and is similar to the real-life. Further, the control parameters work superior in controlling the spreading of rumors. Finally, the numerical results are verified by the analytical results.
The rapid development of social networks makes the rumour, other false news disseminate to the people in a short period. Online users in social networks are dynamically changing the connectivity over time. The effect of dynamic connections results in stochastic variation which is termed as noise. In this paper, a nonlinear rumour propagation model is formulated, the basic regeneration number [Formula: see text] of the proposed model is computed and the stability for the model is discussed. Further, we extend the model to stochastic rumour propagation for online social networks incorporating noise. The existence and uniqueness of the stochastic rumour propagation for the homogeneous network are investigated. Optimal control strategy of stochastic rumour spreading model in online social network is investigated to control the parameters. A comparison between deterministic and stochastic rumour spreading model in online social network is numerically illustrated.
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