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An Agent-Based Modeling Perspective of Understanding the Dynamic Spread of Misinformation and Its Correction on Social Networks

Fri, May 25, 9:30 to 10:45, Hilton Prague, Floor: LL, Vienna


As the citizens' news consumption is increasingly driven by online sources, the propagation of misinformation and “fake news” on those platforms become an increasing concern for the public. Yet, what we know about the phenomena is largely based on anecdotal evidence, therefore its etiology is not yet clearly understood. This study aims to offer a more systematic assessment of underlying mechanisms of misinformation spreading and its correction, combining a macro supply factor and individuals' cognitive basis of adopting misinformation into an integrated, dynamic system model perspective. We first comprehensively review the extant research concerning misinformation and its propagation. Next, relying on agent-based simulations based on a well-known class of an epidemic model of virus infection and recovery, we further explore various boundary conditions of such dynamics, aiming to uncover how and when such misinformation propagates into the public, as well as what factors facilitate or hinder such diffusion processes.