Rumor model on homogeneous social network incorporating delay in expert intervention and government action

Rumors are spreading all over the network drastically, affecting millions of people in a minuscule instance. This malicious news can be a cause of panic, social unrest, political imbalance, and slow economic growth of the country. Epidemiological modeling is a valuable tool to describe not only the dynamics of rumor on a social network but also analyzing the effect of various control strategies for handling emergencies. The time delay is viewed as a latent period and immune period in epidemics. Similarly, time delay exists in rumor spreading on the social network not only to influence thinkers by rumor adopters but also in expert intervention and government policy. On the basis of these premises, we propose a computational mathematical model of malicious news dynamics on a homogeneous social network and demonstrate the effect of delay in expert intervention and government action. Here, we observe that it is difficult to judge the opinion of the social network user about any particular event, if experts take more time to respond and are not continuously active to make aware of the newcomers. Also, social network data become unpredictable, so this work can be helpful for the information security of social network data. The condition of existence and stability of steady states are studied. We also evaluate the Hopf bifurcation condition and calculate the critical value of delay in expert intervention. Moreover, we recognize the most sensitive parameter to the system and numerically simulate the model with some useful parameter sets to justify the theoretical findings. (C) 2020 Elsevier B.V. All rights reserved.