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This study examines how English-language online news and information outlets used visual material in covering the April 2024 floods in Kazakhstan. A quantitative content analysis of 73 illustrated articles from 10 outlets (1 April–31 May 2024) coded 18 article-level variables on format, depicted subjects, emotional intensity, captioning, attribution and indicators of potential ethical concern; the figures therefore describe illustrated coverage, not all flood reporting. Photographs appeared in 98.6% of articles and video in 23.3%. Outlets differed most in format: no Astana Times article (n = 40) carried article video, a gallery or drone footage, whereas RFE/RL (n = 18) and Al Jazeera (n = 7) used these formats and user-generated content more often. Differences in the subjects shown and in emotional intensity were not statistically significant, although these comparisons had limited power. Maps (13.7%) and infographics (one article) were uncommon in every phase and did not increase in the Recovery phase. In exploratory phase comparisons, only a decline in the depiction of rescue workers held with outlet constant, and it did not survive correction for multiple testing. No AI-generated imagery was detected. Drawing on phase models of crisis communication and on cognitive load theory, we offer considerations for newsroom planning during natural disasters.
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Zholzhanova et al. (2026) studied this question.
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