The COVID-19 pandemic highlighted how individual beliefs and behaviors can significantly influence the course of an epidemic. In this paper, we propose a kinetic model that associates the spread of infectious diseases with the dynamics of opinion evolving on social networks. The model captures how information and attitudes toward protective measures change in response to social influence, particularly in environments characterized by digital platforms and varying levels of connectivity. By extending classical compartmental models to include socially structured behavior, we account for the role of influential individuals and the stratified nature of online communication. Using real social media data, we calibrate the model to explore how changes in opinion contribute to the emergence and recurrence of epidemic waves. The results provide a richer understanding of the feedback between social behavior and disease dynamics, with implications for designing more effective public health interventions.