A study by independent computational researcher Mohamed Soufan analyzing 16,695 Arabic-language tweets about Lebanon found that posts expressing uncertainty generate significantly higher engagement than posts written with certainty, despite representing a minority of total posts. The study found that although only 29.9% of tweets contained uncertainty-related language, these tweets received about 51.5% higher mean engagement and approximately 25% higher expected engagement after statistical controls. The research describes this pattern as the Uncertainty-Reply Asymmetry, where posts expressing uncertainty generate disproportionately more replies and conversational interaction online.
The findings indicate that uncertain posts may play a larger role in shaping online discussions than their relatively small share of total posts might imply.
Study of Arabic Tweets About Lebanon
The study conducted by Mohamed Soufan examined 16,695 Arabic-language tweets related to Lebanon collected over a 35-day period. The research aimed to understand how linguistic uncertainty affects engagement and interaction on social media platforms, particularly on X (formerly Twitter).
Tweets were analyzed for linguistic markers indicating uncertainty, such as expressions of doubt, speculation, possibility, or incomplete information.
Figure: Share of Arabic-language tweets containing linguistic uncertainty markers in the dataset (16,695 tweets about Lebanon).
These types of expressions are common in online discussions, especially when users discuss political events, economic issues, or breaking news.
Engagement was measured as the combined total of likes, reposts, and replies. The analysis also used statistical regression models that controlled for tweet length, the presence of URLs, and account verification status to ensure that the relationship between uncertainty and engagement was not explained by other factors.
Key Findings From the Study
Figure: Engagement comparison between uncertain and certain tweets across likes, reposts, and replies.
The study produced several notable findings about the relationship between uncertainty and engagement in Arabic-language discussions about Lebanon.
First, uncertain tweets represented a minority of posts. Approximately 29.9% of tweets in the dataset contained linguistic uncertainty markers, meaning that most tweets were written in a more confident or definitive tone.
However, despite representing less than one-third of the dataset, uncertain tweets received significantly higher engagement. On average, tweets expressing uncertainty received about 51.5% higher mean total engagement compared to tweets written with certainty.
Statistical regression models confirmed this relationship. After controlling for tweet length, URL presence, and account verification status, tweets containing uncertainty were associated with approximately 25% higher expected engagement.
The increase in engagement was not evenly distributed across interaction types. The strongest increase was observed in replies, followed by reposts, while likes showed the smallest difference. This suggests that uncertainty may encourage conversation and interaction rather than just passive reactions.
Minority Posts With Larger Impact
One of the most interesting findings of Mohamed Soufan’s study is that uncertain posts appear to have a disproportionate impact on online discussions.
Although only about 29.9% of tweets contained uncertainty, these posts generated much higher engagement and significantly more replies. This means that a relatively small share of posts may play a larger role in driving discussion and interaction online.
This finding challenges the assumption that the most confident or definitive statements dominate online discussions. Instead, posts expressing uncertainty and open-ended interpretations may encourage more participation and discussion, giving them a larger influence on how conversations develop online.
The Uncertainty-Reply Asymmetry
Figure: The Uncertainty-Reply Asymmetry: uncertainty increases replies more than other interaction types, indicating that uncertain posts encourage conversation rather than passive engagement.
Mohamed Soufan describes this pattern as the Uncertainty-Reply Asymmetry, a phenomenon where posts expressing uncertainty generate disproportionately more replies compared to posts written in a more certain tone.
While uncertain tweets received higher engagement overall, the difference was especially large in replies rather than likes. This indicates that uncertainty may encourage users to respond, comment, or participate in discussions rather than simply reacting with a like.
According to Soufan, uncertainty changes the structure of interaction by keeping discussions open rather than closing them with definitive statements.
“A definitive statement tends to close discussion, while a post that expresses uncertainty signals that the conversation is still open and invites others to respond. The uncertainty itself becomes a prompt for replies,” said Mohamed Soufan.
The Uncertainty–Reply Asymmetry suggests that uncertainty may play an important role in shaping online discussions by encouraging conversational interaction and replies. This pattern may help explain how discussions evolve on social media platforms, where conversation and interaction often develop around uncertain or speculative information rather than definitive statements.
Why Uncertainty Encourages Replies
There are several possible explanations for why uncertain posts generate more replies and interaction online.
One explanation is that uncertain statements leave room for interpretation and discussion. When a post expresses doubt or speculation, other users may feel more inclined to respond with their opinions, corrections, or additional information.
Another explanation is that uncertainty may signal that a topic is unresolved or unclear, which encourages users to participate in the discussion. In contrast, confident or definitive statements may signal that the topic is settled, which may reduce the need for further discussion.
Uncertainty may also increase curiosity and attention. When information is presented as uncertain, users may be more likely to ask questions, seek clarification, or engage in conversation. This may lead to more replies and more interactive discussions rather than passive engagement.
Why This Matters for Online Discussions
Understanding how language affects engagement and discussion is important for studying online communication, political discussions, and information spread on social media platforms.
Social media platforms have become major spaces for public debate, news discussions, and political communication. Small differences in language, such as expressing certainty or uncertainty, may influence how people respond, how discussions develop, and how information spreads online.
The findings of Mohamed Soufan’s study suggest that uncertainty may play a larger role in shaping online discussions than previously assumed. Even though uncertain posts represent a minority of content, they may have a disproportionate influence on conversation and interaction.
This research contributes to a growing field of computational social science that uses large-scale social media data to study communication patterns, online behavior, and digital discussions.
The full research paper, Linguistic Uncertainty and Engagement in Arabic-Language X Discourse by Mohamed Soufan, is available on arXiv.
About Mohamed Soufan
Mohamed Soufan is an independent computational researcher and software engineer from Lebanon whose work focuses on data analysis, computational research, and digital systems. His research examines how language, uncertainty, online behavior, and information spread can be studied using large-scale data and computational methods. Soufan publishes research papers, data analyses, and computational studies exploring digital communication, social media behavior, artificial intelligence, and data-driven research methods.