On the modeling and verification of the spread of fake news, algebraically

In recent years, one of the major issues concerning the study of online social network phenomena is related to the diffusion of misinformation, commonly known as fake news. In the literature, several mathematical tools are used to investigate both the identifying attributes of fake news and their spreading model. This work concentrates on the latter aspect and follows the lines of research inspired by the analysis of epidemic models. Its main contribution is the definition of a modeling framework based on process algebra for the explicit, formal representation of typical behavioral patterns of agents in social networks, and the use of a probabilistic verification framework based on modal logics and model checking for the quantitative analysis of the fake news spread.