Information Acquisition and Risk Screening for Social Media Misinformation During Major Emergencies
Major emergencies generate an acute demand for timely and reliable information while simultaneously amplifying the risk of misinformation diffusion on social media platforms. The regulator therefore needs not only to identify individual pieces of misinformation but also to infer a platform’s privately known misinformation-risk type. We develop a mechanism-design model in which verifiable collaborative disclosure and external monitoring jointly reduce unidentified misinformation and support platform risk screening. Three mechanisms are examined: screening based on disclosure–monitoring bundles, disclosure-only regulation, and ex-post auditing supported by credible penalties. Under the specified incentive and feasibility conditions, screening produces different equilibrium regimes as the platform’s commercial return from unidentified misinformation changes. A central result is counterintuitive: the high-risk platform may optimally face lower disclosure and monitoring requirements because this limits the information rent earned by the low-risk platform. We further show that differentiated and uniform disclosure-only arrangements yield the same optimal expected regulatory payoff, while screening can outperform disclosure-only regulation. When screening and ex-post auditing both satisfy their respective optimality and feasibility conditions, their relative performance depends on a critical auditing-cost threshold and distinct participation requirements. These findings provide insights into coordinating information acquisition and risk screening under asymmetric information.
Authors
- Xin Cui (ORCID: https://orcid.org/0000-0002-6114-9031)
- Qingchun Meng (ORCID: https://orcid.org/0000-0001-5498-3215)
- Guangzheng Sun
Institutions
- Shandong University (CN)
Publication Details
- Journal
- Systems
- Published
- 2026-11-09
- DOI
- https://doi.org/10.3390/systems14111435
- Primary Topic
- Misinformation and Its Impacts
- Type
- article
- Field-Weighted Citation Impact
- 0.00