Disinformation in Social Networks and Bots: Simulated Scenarios of Its Spread from System Dynamics

Alfredo Guzmán Rincón,Nuria Segovia-García,Ruby Lorena Carrillo Barbosa,David Ricardo Africano Franco

doi:10.3390/systems10020034

Alfredo Guzmán Rincón, Nuria Segovia-García + Show 2 more

Open Access

https://doi.org/10.3390/systems10020034

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Journal: Systems	Publication Date: Mar 10, 2022
Citations: 1	License type: CC BY 4.0

Affiliation: University of Applied and Environmental Sciences

Abstract

Social networks have become the scenario with the greatest potential for the circulation of disinformation, hence there is a growing interest in understanding how this type of information is spread, especially in relation to the mechanisms used by disinformation agents such as bots and trolls, among others. In this scenario, the potential of bots to facilitate the spread of disinformation is recognised, however, the analysis of how they do this is still in its initial stages. Taking into consideration what was previously stated, this paper aimed to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature. For achieving the purpose, System dynamics was used as the main modelling technique. The results present a mathematical model, as far as disinformation by this mechanism is concerned, and the simulations carried out against the increase in the rate of activation and deactivation of bots. Thus, the preponderant role of social networks in controlling disinformation through this mechanism, and the potential of bots to affect citizens, is recognised.

Highlights

The academic community has shown widespread interest in understanding how disinformation spreads in virtual media, including social networks, e.g., [1–7], due to the potential of disinformation to trigger various problems for governments, citizens, and other social actors [2]
The aim of this article was to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature
The aim of this article was to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature, so the main technique used for the development of the model was System Dynamics, considering Bala et al [47] and Bianchi [48] as theoretical references

Summary

Introduction

The academic community has shown widespread interest in understanding how disinformation spreads in virtual media, including social networks, e.g., [1–7], due to the potential of disinformation to trigger various problems for governments, citizens, and other social actors [2]. An example of this was the case of COVID-19, when the Russian media RT and Sputnik accused NATO and the United States of America of creating the virus in order to destabilise the Chinese economy, and this information was widely spread on social networks such as Facebook, Twitter and Tik Tok [3,10], or, in the case of the vaccines developed for COVID-19, where the anti-vaccine movement sought to attribute effects such as autism and possible genetic malformations to their use, triggering mistrust on the part of the population and preventing the control of the virus and the mitigation of its transmission [11] In view of these examples, one of the main problems for social actors, in particular states, as well as the academic community, is the lack of awareness of the existence of this type of information and the lack of understanding of the strategies used by the disinformation agent to ensure the propagation of misinformation on social networks [12–14]. An example of this is Twitter, where, given the importance of this network in issues related to politics, it has been estimated that between 9% and 15% of active accounts are bots [15–18]

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