Prebunking Design as a Defense Mechanism Against Misinformation Propagation on Social Networks

TL;DR

This paper models and optimizes prebunking strategies to effectively counter misinformation spread on social networks, balancing timely accurate information delivery with user experience considerations.

Contribution

It formalizes the prebunking problem as an optimal timing policy using epidemiological modeling and proposes an approximate solution that reduces user disruption.

Findings

Policy halves the user experience cost of repeated information delivery.

Optimal prebunking timing outperforms immediate correction strategies.

Model effectively balances misinformation mitigation and user experience.

Abstract

The growing reliance on social media for news consumption necessitates effective countermeasures to mitigate the rapid spread of misinformation. Prebunking, a proactive method that arms users with accurate information before they come across false content, has garnered support from journalism and psychology experts. We formalize the problem of optimal prebunking as optimizing the timing of delivering accurate information, ensuring users encounter it before receiving misinformation while minimizing the disruption to user experience. Utilizing a susceptible-infected epidemiological process to model the propagation of misinformation, we frame optimal prebunking as a policy synthesis problem with safety constraints. We then propose a policy that approximates the optimal solution to a relaxed problem. The experiments show that this policy cuts the user experience cost of repeated information delivery in half, compared to delivering accurate information immediately after identifying a misinformation propagation.