Controlling the Misinformation Diffusion in Social Media by the Effect of Different Classes of Agents

TL;DR

This paper extends a SIR-based misinformation model to real social networks by incorporating different agent classes and proposes strategies like education and fact-checker bots to effectively control misinformation spread.

Contribution

It introduces a novel extension of the SBFC model to include diverse agent classes and evaluates two strategies for controlling misinformation in social networks.

Findings

Both education of influential agents and adding fact-checker bots effectively reduce misinformation spread.

The extended model accurately captures real social network dynamics.

Control strategies significantly improve fact verification and reduce belief in false news.

Abstract

The rapid and widespread dissemination of misinformation through social networks is a growing concern in today's digital age. This study focused on modeling fake news diffusion, discovering the spreading dynamics, and designing control strategies. A common approach for modeling the misinformation dynamics is SIR-based models. Our approach is an extension of a model called 'SBFC' which is a SIR-based model. This model has three states, Susceptible, Believer, and Fact-Checker. The dynamics and transition between states are based on neighbors' beliefs, hoax credibility, spreading rate, probability of verifying the news, and probability of forgetting the current state. Our contribution is to push this model to real social networks by considering different classes of agents with their characteristics. We proposed two main strategies for confronting misinformation diffusion. First, we can educate a minor class, like scholars or influencers, to improve their ability to verify the news or remember their state longer. The second strategy is adding fact-checker bots to the network to spread the facts and influence their neighbors' states. Our result shows that both of these approaches can effectively control the misinformation spread.