01328nas a2200133   4500008004100000245005300041210005300094260001300147520090400160100002301064700001901087700002101106856006701127       2020                        eng d00aOpinion Dynamic Modeling of Fake News Perception0 aOpinion Dynamic Modeling of Fake News Perception  bSpringer3 aFake news diffusion represents one of the most pressing issues of our online society. In recent years, fake news has been analyzed from several points of view, primarily to improve our ability to separate them from the legit ones as well as identify their sources. Among such vast literature, a rarely discussed theme is likely to play uttermost importance in our understanding of such a controversial phenomenon: the analysis of fake news’ perception. In this work, we approach such a problem by proposing a family of opinion dynamic models tailored to study how specific social interaction patterns concur to the acceptance, or refusal, of fake news by a population of interacting individuals. To discuss the peculiarities of the proposed models, we tested them on several synthetic network topologies, thus underlying when/how they affect the stable states reached by the performed simulations.1 aToccaceli, Cecilia1 aMilli, Letizia1 aRossetti, Giulio  uhttps://link.springer.com/chapter/10.1007/978-3-030-65347-7_31