{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T02:10:24Z","timestamp":1792462224331,"version":"4.5.0"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T00:00:00Z","timestamp":1747353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>This paper investigates the spatial\u2013temporal dynamics of disaster risk diffusion and the dissemination of emergency knowledge during Typhoon Yagi, one of the strongest autumn typhoons to hit China since 1949. Employing the spatial\u2013temporal dynamics approach, the study utilizes social media data from Sina Weibo, collected through Python crawling, to analyze the diffusion process of typhoon disaster risks and the mechanism of emergency knowledge dissemination. The research examines the spatial\u2013temporal characteristics of disaster risk diffusion and emergency knowledge dissemination, their interrelationships, and the influence of social background and geographical environment. The findings reveal that the public\u2019s discussion on disaster risk and emergency knowledge changes over time, with distinct patterns observed during the typhoon warning, occurrence, and recovery periods. Spatially, Guangdong and Hainan provinces show the highest levels of discussion, aligning with the typhoon\u2019s landfall locations. The study underscores the co-evolutionary nature of disaster risk diffusion and emergency knowledge dissemination, whereby the dissemination of emergency knowledge is concomitant with the diffusion of typhoon risk. This research provides a theoretical foundation for the field of disaster risk management and emergency knowledge dissemination, offering practical references for future responses to natural risks.<\/jats:p>","DOI":"10.3389\/fpubh.2025.1528199","type":"journal-article","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T05:22:22Z","timestamp":1747372942000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Analyzing the spatial\u2013temporal dynamics of disaster risk based on social media data: a case study of Weibo during the Typhoon Yagi period"],"prefix":"10.3389","volume":"13","author":[{"given":"Xingqi","family":"Zou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxin","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,5,16]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"3225","DOI":"10.1007\/s11069-022-05804-y","article-title":"Damage analysis of retired typhoons in mainland China from 2009 to 2019","volume":"116","author":"Wan","year":"2023","journal-title":"Nat Hazards"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"446","DOI":"10.3390\/make4020020","article-title":"Machine learning in disaster management: recent developments in methods and applications","volume":"4","author":"Linardos","year":"2022","journal-title":"Machine Learning Knowledge Extraction"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"3443","DOI":"10.1007\/s00521-021-05757-6","article-title":"Flood disaster risk assessment based on random forest algorithm","volume":"34","author":"Zhu","year":"2022","journal-title":"Neural Comput & Applic"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.geomorph.2006.03.015","article-title":"Temporal and spatial trends of precipitation and river flow in the Yangtze River basin, 1961\u20132000","volume":"85","author":"Jiang","year":"2007","journal-title":"Geomorphology"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"3316","DOI":"10.1175\/2009JCLI3130.1","article-title":"Intensification of east Asian summer rainfall interannual variability in the twenty-first century simulated by 12 CMIP3 coupled models","volume":"23","author":"Lu","year":"2010","journal-title":"J Clim"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.gloplacha.2015.05.007","article-title":"Spatiotemporal behavior of floods and droughts and their impacts on agriculture in China","volume":"131","author":"Zhang","year":"2015","journal-title":"Glob Planet Chang"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"101031","DOI":"10.1016\/j.uclim.2021.101031","article-title":"Spatial and temporal distribution characteristics of haze and pollution particles in China based on spatial statistics","volume":"41","author":"Liu","year":"2022","journal-title":"Urban Clim"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"108723","DOI":"10.1016\/j.ress.2022.108723","article-title":"An event-driven probabilistic methodology for modeling the spatial-temporal evolution of natural hazard-induced domino chain in chemical industrial parks","volume":"226","author":"Men","year":"2022","journal-title":"Reliability Engineering System Safety"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"101744","DOI":"10.1016\/j.ijdrr.2020.101744","article-title":"Impact of information seeking, disaster preparedness and typhoon emergency response on perceived community resilience in Hong Kong","volume":"50","author":"Guo","year":"2020","journal-title":"Int J Disaster Risk Reduction"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"1276083","DOI":"10.3389\/fpubh.2023.1276083","article-title":"Public opinion communication mechanism of public health emergencies in Weibo: take the COVID-19 epidemic as an example","volume":"11","author":"Ren","year":"2023","journal-title":"Front Public Health"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"9148","DOI":"10.3390\/su14159148","article-title":"Framing disaster risk perception and vulnerability in social media communication: a literature review","volume":"14","author":"Morelli","year":"2022","journal-title":"Sustain For"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"102783","DOI":"10.1016\/j.ijdrr.2022.102783","article-title":"Social media use in disaster recovery: a systematic literature review","volume":"70","author":"Ogie","year":"2022","journal-title":"Int J Disaster Risk Reduction"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"103207","DOI":"10.1016\/j.ijdrr.2022.103207","article-title":"How do Australians use social media during natural hazards? 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