Recently, information spreads swiftly and widely through social media and other online platforms. However, this rapid flow of information is often followed by an increasing circulation of inaccurate or misleading content, commonly known as hoaxes. A hoax refers to false, deceptive, or unfounded information that is spread either intentionally or unintentionally. Typically, hoaxes are crafted in such a way that they appear to be credible news, with the aim of influencing public perception, spreading disinformation, or gaining political or economic advantages. This research investigates the spread of hoaxes within human populations based on a transmission model developed in earlier studies. The main contribution of this work lies in refining the model by incorporating an education parameter as a control strategy to identify the optimal level of education required to reduce the dissemination of hoaxes. The optimal control approach applied is the Pontryagin minimum principle. The model also takes into account both asymptomatic and symptomatic infected individuals, including the transition from asymptomatic to symptomatic cases. Numerical simulations demonstrate that applying this control strategy results in a faster decrease in the number of symptomatic infected individuals compared to conditions without any control intervention
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