Crowd-sourced fact-checking

Methods and systems that leverage community members to identify misinformation and flag stories for verification. This includes both explicit flagging mechanisms (where users mark content as false) and implicit signals (engagement patterns that indicate distrust or skepticism).

Key videos

• Rand — How Polarization May Help Combat Misinformation — Theoretical and empirical work on scaling fact-checking through crowd-sourced systems; demonstrates that polarized individuals are effective at flagging false content

Key papers

• Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation — Uses stochastic optimal control to decide which flagged stories to send for fact-checking, minimizing misinformation spread.

Related topics

• Fact-checking and corrections (broader)
• Crowdsourcing (mechanism)
• Misinformation interventions (goal)