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

TL;DR

This study shows that AI-generated credibility signals significantly influence social media news perception, reducing partisan bias and distrust more effectively than traditional engagement metrics, highlighting AI's persuasive power in online information.

Contribution

The paper introduces large-scale experimental evidence that AI credibility signals outperform engagement metrics in shaping news perception and trust.

Findings

AI credibility signals reduce partisan bias

AI feedback surpasses likes and shares in influence

Generative AI has strong persuasive effects

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.