Social media platforms struggle with the rapid spread of misinformation, where false claims and misleading content often gain traction before being fact-checked. Current engagement metrics don’t distinguish between genuine interactions and engagement with questionable content, making it harder for users to identify trustworthy information.

A Crowd-Sourced Approach to Flag Misinformation

One way to address this problem could be by introducing a "fake" button alongside traditional engagement options (like, share, etc.). This would let users flag content they believe is misleading. When enough users flag a post, the platform could:

• Add a temporary "potentially misleading" label pending review
• Reduce its visibility in feeds
• Attach fact-checking resources

To prevent misuse, safeguards like requiring multiple unique flaggers and weighting input from trusted accounts more heavily could be implemented. Clear guidelines and an appeals process would help ensure fairness.

How It Differs from Existing Solutions

Current approaches, such as Facebook’s fact-checking partners or Twitter’s Community Notes, rely on professionals or contextual annotations. A user-driven flagging system could offer a faster, more scalable way to identify suspicious content early. Unlike Reddit’s report feature (buried in menus), this would make misinformation reporting more accessible.

Potential Execution Strategy

A minimal version could start with a simple flagging button that collects data without consequences. If successful, thresholds for temporary labels could be introduced, followed by integration with fact-checkers. Gradually, algorithms could reduce the reach of frequently flagged content while monitoring for abuse.

This approach could empower users to participate in content moderation while helping platforms balance engagement with credibility—potentially reducing misinformation’s harmful effects at scale.