Linguistic Uncertainty and Reply Engagement on X: A Cross-Domain Replication of the Uncertainty-Reply Asymmetry
For social media researchers and platform designers, this work replicates a known phenomenon in a new linguistic and topical context, showing the effect is not limited to Arabic or specific domains.
This paper tests whether the Uncertainty-Reply Asymmetry—where uncertain posts receive more replies—replicates in English-language social media posts on economic and political topics. Analyzing 2,258 posts, they find uncertain posts receive 82% more replies on average, with a statistically significant regression coefficient (β=0.126, p=0.011), confirming the pattern across languages and domains.
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.