ArticleSN partial differential equations and applications2022
From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications.
Article in SN partial differential equations and applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Exploring agent interaction patterns in the comment sections of fake and real news.Journal of the Royal Society, Interface · 2024Article
- An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion.PeerJ. Computer science · 2023Article
- Modeling opinion polarization on social media: Application to Covid-19 vaccination hesitancy in Italy.PloS one · 2023Article
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Authors and funding
3 authors.
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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.
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