Analysing Information Diffusion in Natural Hazards using Retweets - a Case Study of 2018 Winter Storm Diego

Information diffusion on social media during disasters is an important indicator of community resilience. As a common natural hazard in the U.S., winter storms often cause adverse socio-economic impacts human society. Understanding people’s perception and behaviours to mitigate negative promote This study applies text mining spatial analysis methods Twitter data Winter Storm Diego 2018 December. Different from previous studies focusing original tweets, this utilized retweets model information contiguous United States analysed geographic distribution flows various topics. The extent direction storm-related were compared among different Kernel density maps standard deviational ellipse applied result shows that people outside affected areas expressed more sentiment towards storm than areas. Also, distance decay retweet has been found rate differs These findings analyses will provide support for disaster relief, communication broadcasting through platforms.