Spreading of fake news, competence and learning: kinetic modelling and numerical approximation

Abstract

The rise of social networks as the primary means of communication in almost every country in the world has simultaneously triggered an increase in the amount of fake news circulating online. The urgent need for models that can describe the growing infodemic of fake news has been highlighted by the current pandemic. The resulting slowdown in vaccination campaigns due to misinformation and generally the inability of individuals to discern the reliability of information is posing enormous risks to the governments of many countries. In this research using the tools of kinetic theory, we describe the interaction between fake news spreading and competence of individuals through multi-population models in which fake news spreads analogously to an infectious disease with different impact depending on the level of competence of individuals. The level of competence, in particular, is subject to evolutionary dynamics due to both social interactions between agents and external learning dynamics. The results show how the model is able to correctly describe the dynamics of diffusion of fake news and the important role of competence in their containment. This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.

From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications

“…In this section we present a model for the description of the spreading of fake news in a society characterized by a heterogeneous competence of agents. Our starting point is the compartmental kinetic approach recently proposed in [ 19 ]. We suppose that the system of agents can be divided in the following epidemiologically relevant states: susceptible (S) agents are the ones that are unaware of fake news, we further denote as exposed (E) the agents that encountered the fake news but have still to spread them, infectious (I) agents are the real spreader and, finally, the removed (R) agents are not actively engaged in the spread of misinformation.…”

“…We suppose that the process defined in (ii) takes place in a different time scale from the one of interactions between agents. In particular, unlike [ 19 ] we assume that the time scale of online interactions for competence formation is faster than interactions with the social background. To this end, we will consider advection terms that will be defined in the next section.…”

“…In [ 19 ], starting from an agent-based model for the dissemination of fake news in presence of competence, using the tools of kinetic theory, in the limit of a large number of agents, novel mathematical models were proposed and discussed. Previously, kinetic models that include the role of competence or knowledge had been proposed in [ 5 , 29 , 31 ].…”

“…The compartmental structure of the model for fake-news spreading in presence of competence introduced in [ 19 ] is composed by four groups of individuals: the susceptible (S) agents—defined as the ones who are unaware of the fake news; the exposed (E) agents—those who know the news but still have not decide whether to spread it or not; the infectious (I) agents—who actively divulge and finally the skeptical or removed (R) agents—those who are aware of the news but choose to not spread it. On a population divided among such categories, there is also a social structure based on an additional time evolving variable that measures the competence level of the agents.…”

Kinetic exchange models of societies and economies

“…In Franceschi & Pareschi’s contribution [ 32 ], compartmental epidemiology models are used to study the propagation of fake news. Indeed, the rise of social networks as a primary means of communication has simultaneously triggered an increase in the amount of fake news circulating online.…”