Mitigating Influence of Disinformation Propagation Using Uncertainty-Based Opinion Interactions

For decades, the spread of disinformation in online social networks (OSNs) has been a serious issue. Disinformation via media can easily mislead people’s beliefs toward or against an event that may their behaviors based on misbeliefs. The game theory approaches have proposed under dynamic settings to limit adverse influences disinformation. It is challenge expand users’ strategies from spreading decisions possible opinion updating choices. This work proposes game-theoretic framework formulate opinions by belief model called Subjective Logic (SL) and provide updates five types interactions OSN platforms. are updated user choices through among legitimate users, attackers, defender OSN. Via extensive simulation experiments, effectiveness models decision-makers (DMs) analyzed terms users believing disbelieving epidemic with parameter optimization. Our results show while homophily-based DMs (H-DMs) introduce highest polarization, uncertainty-based (U-DMs) effectively filter untrustworthy propagating