Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

Abstract

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

FOMO (fate of online media only) in infectious disease modeling: a review of compartmental models

“…As primary drivers of the spread of misinformation [ 71 ], they are often overlooked—perhaps due to their novelty and stealth like modus operandi. While we were able to find agent-based models [ 72 ], further research is needed for their incorporation into compartmental information models and thereafter into coupled models of disease transmission.…”

El fact-checking en castellano

“…Es allí donde se cuece el caldo de cultivo para la desinformación. La preocupación fundamental radica en el hecho de que, como señalan diversas investigaciones (Fernández-García, 2017;Lotito et al, 2021;Vosoughi et al, 2018;Zhao et al, 2020;entre otros)…”

Digital society social interactions and trust analysis model

“…The simulation model or mathematical model should have features such as demonstrating two-way communications ie ., the influence between digital communication and epidemic and vice versa . Finally, it must help the users to build a decision support system that appropriates multiple psychological/social ( Lotito, Zanella & Casari, 2021 ) models that help to reduce friction and improve trust in the society. An explorative analysis of this expected model shows that no single equation model or single approach model will be useful in building a comprehensive model ( Lotito, Zanella & Casari, 2021 ; Zhao et al, 2020 ).…”