How the hesitation mechanism suppresses misinformation spreading on time-varying networks

Misinformation spreading on social media is generally restricted by a variety of factors such as the underlying network properties and user behaviors. We consider a part of users have skeptical or critical attitudes to misinformation. We propose a novel ignorant–hesitator–spreader–recovery (IHSR) spreading model on time-varying networks with a hesitation mechanism characterized by the proportion of skeptical nodes (users) and their skepticism level. Using a mean-field approach and Monte Carlo simulations, we verify the correctness of our model and investigate how the hesitation mechanism suppresses misinformation spreading, in terms of spreading threshold and the final prevalence of misinformation. It is shown that with the increase of the proportion of skeptical users and the increase of the skepticism level, the spreading threshold becomes greater and the final prevalence is significantly reduced. We also compare the impacts of three selection strategies of skeptical nodes on the final prevalence. Interestingly, a counterintuitive result is obtained that prioritizing selecting nodes with a smaller activity works best for suppressing misinformation, and by contrast prioritizing selecting nodes with a larger activity is worst.