From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications
arXiv:2202.10809 · doi:10.1007/s42985-022-00194-z
Abstract
Fake news spreading, with the aim of manipulating individuals' perceptions of facts, is now recognized as a major problem in many democratic societies. Yet, to date, little has been understood about how fake news spreads on social networks, what the influence of the education level of individuals is, when fake news is effective in influencing public opinion, and what interventions might be successful in mitigating their effect. In this paper, starting from the recently introduced kinetic multi-agent model with competence by the first two authors, we propose to derive reduced-order models through the notion of social closure in the mean-field approximation that has its roots in the classical hydrodynamic closure of kinetic theory. This approach allows to obtain simplified models in which the competence and learning of the agents maintain their role in the dynamics and, at the same time, the structure of such models is more suitable to be interfaced with data-driven applications. Examples of different Twitter-based test cases are described and discussed.
arXiv commentMinor changes to align the manuscript to its published version
References in corpus (12)
- On a kinetic model for a simple market economy
- Structure preserving schemes for nonlinear Fokker-Planck equations and applications
- Wealth distribution and collective knowledge. A Boltzmann approach
- Modeling the spread of fake news on Twitter
- Opinion modeling on social media and marketing aspects
- Opinion dynamics: inhomogeneous Boltzmann-type equations modelling opinion leadership and political segregation
- Optimal control of epidemic spreading in presence of social heterogeneity
- Kinetic models of collective decision-making in the presence of equality bias
- Kinetic modelling of epidemic dynamics: social contacts, control with uncertain data, and multiscale spatial dynamics
- Spreading of fake news, competence, and learning: kinetic modeling and numerical approximation
- Reducing complexity of multiagent systems with symmetry breaking: an application to opinion dynamics with polls
- On a kinetic opinion formation model for pre-election polling