AI Credibility Signals Outrank Institutions and Engagement in Shaping News Perception on Social Media

• URL: http://arxiv.org/abs/2511.02370v1
• Date: Tue, 04 Nov 2025 08:46:54 GMT
• Title: AI Credibility Signals Outrank Institutions and Engagement in Shaping News Perception on Social Media
• Authors: Adnan Hoq, Matthew Facciani, Tim Weninger,
• Abstract summary: We present a large-scale mixed-design experiment investigating how AI-generated credibility scores affect user perception of political news.<n>Our results reveal that AI feedback significantly moderates partisan bias and institutional distrust, surpassing traditional engagement signals such as likes and shares.
• Score: 4.197003225775791
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: AI-generated content is rapidly becoming a salient component of online information ecosystems, yet its influence on public trust and epistemic judgments remains poorly understood. We present a large-scale mixed-design experiment (N = 1,000) investigating how AI-generated credibility scores affect user perception of political news. Our results reveal that AI feedback significantly moderates partisan bias and institutional distrust, surpassing traditional engagement signals such as likes and shares. These findings demonstrate the persuasive power of generative AI and suggest a need for design strategies that balance epistemic influence with user autonomy.

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