  When considering a specific event, news that accurately reflects the ground
truth is deemed as real information, while news that deviates from the ground
truth is classified as false information. False information often spreads fast
due to its novel and attention-grabbing content, which poses a threat to our
society. By extending the Susceptible-Infected (SI) model, our research offers
analytical decision boundaries that enable effective interventions to get
desirable results, even when intermediate functions cannot be analytically
solved. These analytical results may provide valuable insights for policymakers
in false information control. When assessing intervention costs using the
model, the results indicate that the sooner we intervene, the lower the overall
intervention cost tends to be.
