The Confidence – Quality Mismatch: Assertive Language Signals Lower-Quality News

Misinformation on social media threatens democracy, public health, and civic discourse. In fast-paced feeds, users often rely on quick cues when deciding what to attend to, believe, and share. One particularly consequential linguistic cue is confidence—widely treated as a signal of knowledge and credibility. Yet, we show that in social media news contexts, confidence is counterintuitively anti-diagnostic: it signals lower-quality information while also predicting greater diffusion. Using computational linguistics and machine learning, we analyze over 20 million posts across eight major online platforms. Posts expressed with greater confidence are more likely to link to lower-quality, more misinformative news domains, even controlling for user baselines, toxicity, and political lean. At the same time, confident posts also receive more engagement. Together, these findings show that confidence—often treated as a cue to knowledge—acts as an anti-diagnostic signal of information quality while simultaneously predicting the diffusion of misinformation.