Linguistic Uncertainty and Reply Engagement on X: A Cross-Domain Replication of the Uncertainty-Reply Asymmetry

TL;DR

This study confirms that linguistic uncertainty on social media significantly boosts reply engagement across different topics and in English, replicating prior findings from Arabic-language research.

Contribution

It demonstrates that the uncertainty-reply asymmetry is a general phenomenon across languages and domains, using a large cross-domain English-language social media dataset.

Findings

Uncertain posts receive 82% more replies than certain posts.

Regression analysis shows a 13% higher expected reply engagement for uncertain posts.

The asymmetric engagement pattern replicates prior Arabic-language research.

Abstract

Linguistic uncertainty is common in social media, but its relationship with engagement remains unclear across languages and topics. Using 2,258 English-language posts on Federal Reserve policy, inflation, and electoral politics collected over three days in April 2026, we test whether the Uncertainty-Reply Asymmetry observed in prior Arabic-language research replicates in a broader context. Posts are classified using a lexicon-based uncertainty framework, with approximately one-third identified as uncertain. Uncertain posts receive 82% more replies on average than certain posts, with smaller increases in reposts and likes, replicating the asymmetric engagement pattern observed in prior work. Regression results confirm a positive and statistically significant association between uncertainty and replies (\b{eta} = 0.126, p = 0.011), equivalent to ~13% higher expected reply engagement, while total engagement shows a positive but weaker association. These findings suggest that linguistic uncertainty systematically increases conversational engagement and may reflect a general interactional mechanism across languages and domains.