arXiv subjects

Mohamed Soufan

Publications and source records attributed to Mohamed Soufan.

5 recordsLinked to original sources

arXiv2026

Visibility Without Guidance: Measuring the Actionability of Public Crisis Communication in Lebanon

Public crisis communication is most valuable when it enables protective action: when it tells affected populations not only what is happening, but where, what to do, how to access help, and whom the guidance applies to. This study examines whether institutional crisis communication in Lebanon during an active conflict escalation met that standard. It presents a systematic actionability audit of 182 public-facing communication items issued by nine Lebanese state institutions, emergency responders, and United Nations humanitarian agencies between April 1 and May 7, 2026. Each item was coded on five binary dimensions: specific location, clear instruction, access channel or contact, time or date reference, and target group identification. An actionability score between 0 and 5 was calculated as the arithmetic sum of the five dimensions, with score consistency mechanically verified across all items. Findings indicate a substantial gap between communicative output and actionable guidance. The mean actionability score was 1.98 out of 5, with 46.7% of items scoring 0 or 1. Access channel or contact information was absent from 89.6% of items. UN humanitarian agencies produced a mean score of 3.10, compared with 1.35 for state and ministry sources, while emergency responders occupied an intermediate position. Communication type analysis shows that informational reporting was more prevalent than operational guidance. The findings suggest that institutional communication during this period was often informative rather than directive, and offer a replicable audit framework for assessing crisis communication adequacy in comparable contexts.

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arXiv2026

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

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.

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arXiv2026

Measuring the Gap Between Media Coverage and Public Information Demand: Evidence from the 2026 Lebanon Conflict

This study examines the relationship between media coverage and public information demand during the Lebanon conflict in March 2026. Using a dataset of 11,623 English-language news articles collected from the GDELT database and Google Trends data for searches conducted within Lebanon, the study compares the distribution of news coverage across topics with the distribution of public search interest. News headlines were filtered for relevance and classified into four categories: Conflict, Economy, Living Conditions, and Emigration. Public information demand was measured using Google Trends topic data for the same categories. The results show a substantial divergence between news coverage and search interest. Conflict accounted for 94.9% of classified news coverage but only 36.9% of total search interest. In contrast, Economy, Living Conditions, and Emigration together accounted for 63.1% of search demand but only 5.1% of news coverage. Time series analysis indicates that search demand for economic and living conditions remained consistently elevated throughout the month rather than reacting to specific conflict events. These findings were robust to the exclusion of the peak conflict period (March 1-5), with Conflict coverage remaining at 94.9% and the information gap persisting across all three under-covered categories. The findings suggest that during the study period, media coverage of Lebanon was heavily concentrated on military events, while public information demand was distributed across economic conditions, daily life, and emigration. This study contributes to agenda-setting research by providing a quantitative comparison between media agenda and public information demand during an active conflict period.

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arXiv2026

The Structure of Participation and Attention in Arabic-Language Hezbollah Discourse on X

Social media platforms play an increasingly important role in shaping political discussion and information flows. This study examines the structure of participation and attention in Arabic-language discourse about Hezbollah on X (formerly Twitter). Using a dataset of 15,767 tweets posted by 8,148 users between March 1 and March 8, 2026, the analysis investigates how engagement is distributed across participants and whether certain types of accounts play a disproportionate role in attracting attention. The results reveal a highly unequal distribution of engagement. Although thousands of users participate in the conversation, the top 1% of users capture 61.5% of all engagement, while the top 10% capture 96.2%. At the same time, most content is produced by non-media users, who account for 89.6% of users and 79.9% of tweets in the dataset. Accounts labeled as media, identified through media-related keywords in account metadata, receive higher engagement per tweet on average (41.32 interactions) than non-media users (30.84 interactions) and are overrepresented among the most engaged accounts. These findings indicate that while Hezbollah-related discourse on X appears broadly participatory in terms of posting activity, audience attention remains strongly concentrated among a small minority of highly visible accounts.

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arXiv2026

Linguistic Uncertainty and Engagement in Arabic-Language X (formerly Twitter) Discourse

Linguistic uncertainty is a common feature of social media discourse, yet its relationship with user engagement remains underexplored, particularly in non-English contexts. Using a dataset of 16,695 Arabic-language tweets about Lebanon posted over a 35-day period, we examine whether tweets expressing linguistic uncertainty receive different levels and forms of engagement compared to certainty-marked tweets. We develop a lexicon-based, context-sensitive classifier to identify uncertainty markers and classify 29.9% of tweets as uncertain. Descriptive analyses indicate that uncertain tweets exhibit 51.5% higher mean total engagement (likes, retweets, and replies). Regression models controlling for tweet length, URL presence, and account verification status confirm a positive association between uncertainty and engagement (\b{eta} = 0.221, SE = 0.044, p < 0.001), corresponding to approximately 25% higher expected engagement. The association is strongest for replies, followed by retweets and likes, suggesting a shift toward more conversational forms of engagement. Results are robust to alternative model specifications and adjustments for within-account correlation. These findings suggest that linguistic uncertainty may function as an interactional cue that encourages participatory engagement in Arabic-language social media discourse. The study contributes computational approaches for modeling linguistic features in large-scale, non-English digital communication.

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