Source and Temporal Patterns in Twitter Risk-Protection Messaging During Cyclone Shaheen in Oman: A Quantitative Content Analysis Guided by the CERC Model

Social media can support rapid warning, information sharing, and public guidance during natural disasters, but communication patterns may vary according to who posts, when messages appear, and what guidance they contain. Guided by the temporal logic of the Crisis and Emergency Risk Communication (CERC) model, this study examined source- and posting-period-based patterns in Twitter communication during Cyclone Shaheen in Oman. A quantitative content analysis was conducted on the final analytic sample of 600 publicly accessible tweets posted between 24 September and 15 October 2021. Stratified random sampling represented five source categories - governmental meteorology, non-meteorological government, media, netizen, and amateur accounts - and three posting periods: before, during, and after the cyclone. Tweets were coded for timeliness, action orientation, format, online attitudinal engagement, and preparedness-, response-, and recovery-related guidance. Intercoder reliability calculated on 50 tweets was 0.82. Overall, 71.0% of tweets were timely, 45.8% were action-oriented, 87.7% combined text and visuals, and 92.0% received at least one like or retweet. Preparedness guidance appeared in 46.8% of tweets, response guidance in 35.7%, and recovery guidance in 45.5%. The four-item composite risk-protection content score differed significantly by posting period, F(2, 597) = 9.26, p < .001, and by source, F(4, 595) = 24.10, p < .001. The highest period mean occurred after the cyclone. Meteorological accounts recorded the highest descriptive source mean, followed by government accounts, with no significant difference between those two sources. The findings are consistent with CERC's phase-sensitive premise and show that risk-protection messaging was distributed across institutional, media, and citizen sources. Likes and retweets are interpreted as online reactions and message amplification, not as evidence of offline protective action.

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