Simulating the influence of Facebook fan pages on individual attitudes toward vaccination using agent-based modelling

Abstract

The anti-vaccination movement is dangerous because of its influence on vaccine hesitancy. Nowadays, social media platforms become significant sources of anti-vaccination information; therefore, combating their proliferation needs to be addressed by the relevant authorities. Previous studies suggested two policies to mitigate the negative influence of anti-vaccination information online: attaching caution banners from healthcare authorities and engaging in censorship of anti-vaccine supporting information providers. However, these recommendations were obtained without considering how the users form their sentiments. In this paper, we explore the influence of the existing network of vaccination-related Facebook pages on an individual user's vaccination sentiment using agent-based modelling (ABM). We use the ABM implementation of the Zaller model to convert the user's information consumption to their vaccination sentiment. Our simulation results show that the application of the two policies leads to improved sentiment on vaccination, reinforcing existing suggestions obtained by different methods.