Community notes reduce engagement with and diffusion of false information online

Area of Science:

• Social Media Analysis
• Information Diffusion Studies
• Computational Social Science

Background:

• Social networks facilitate information spread, with significant research on true vs. false content diffusion patterns.
• Limited understanding exists on how platform interventions impact the engagement and spread of false information.

Purpose of the Study:

• To estimate the causal effects of Community Notes, a crowd-sourced fact-checking feature on X (formerly Twitter), on the diffusion and engagement of false content.
• To quantify the impact of fact-checking interventions on user interactions and content reach.

Main Methods:

• Utilized detailed time series data for 40,078 posts with proposed Community Notes.
• Employed synthetic control methods to estimate counterfactual outcomes for posts with and without fact-checking notes.

Main Results:

• Fact-checking notes significantly reduced engagement: average reductions of 46.1% in reposts, 44.1% in likes, 21.9% in replies, and 13.5% in views immediately after attachment.
• Over the posts' entire lifespans, reductions were estimated at 11.6% fewer reposts, 13.3% fewer likes, 6.9% fewer replies, and 5.5% fewer views.
• Fact-checked content exhibited less deep and viral diffusion cascades, though not less broad, compared to non-fact-checked content.

Conclusions:

• Community Notes effectively mitigate the engagement with and diffusion of false content on social media platforms.
• Fact-checking interventions alter the structural patterns of information diffusion, making cascades less viral.
• The study highlights the potential of platform-based fact-checking mechanisms in combating online misinformation.