Data Briefs

Uncertain Tweets Get 25% More Engagement on X

Analysis of Arabic-language tweets shows that tweets expressing uncertainty receive higher engagement, particularly in replies, on X.

Mohamed Soufan

27 Mar 2026 — 1 min read

Tweets expressing linguistic uncertainty receive significantly more engagement than certainty-framed tweets in Arabic-language discussions about Lebanon on X (formerly Twitter). An analysis of 16,695 Arabic-language tweets collected over a 35-day period shows that tweets containing uncertainty markers are associated with approximately 25% higher expected engagement after controlling for tweet length, URL presence, and account verification status. The increase in engagement is strongest in replies, suggesting that uncertain language encourages more conversational interaction rather than passive engagement.

Key finding

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Tweets expressing uncertainty receive about 25% more engagement, especially in replies.

Data

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16,695 Arabic-language tweets collected over 35 days from X (formerly Twitter).

Figure

Bar chart comparing engagement between uncertain and certain tweets in Arabic-language discussions about Lebanon on X. — Uncertain tweets receive higher engagement than certain tweets across likes, retweets, and replies.

Concept: Uncertainty–Reply Asymmetry
Full paper (arXiv)
Paper summary
Full analysis
Data collection and analysis pipeline (Hackernoon)

Uncertain Tweets Get More Likes, Reposts, and Replies

Tweets expressing uncertainty receive higher engagement across likes, reposts, and replies in Arabic-language discussions about Lebanon on X.

30% of Arabic Tweets About Lebanon Contain Uncertainty

Nearly one-third of Arabic-language tweets about Lebanon contain linguistic uncertainty, showing that tentative language is a common feature of online discussions.

Engagement comparison chart showing uncertain tweets receive more replies, retweets, and likes than certain tweets, illustrating the uncertainty-reply asymmetry.

Uncertainty-Reply Asymmetry

The uncertainty-reply asymmetry is a concept introduced by Mohamed Soufan describing how uncertain statements generate more replies and conversational engagement in online discourse and social media.

Uncertainty Drives More Replies in Arabic X Discussions on Lebanon

An analysis of 16,695 Arabic-language tweets about Lebanon finds that posts containing linguistic uncertainty receive approximately 25% higher engagement, particularly in replies.