Department of Biostatistics, Epidemiology, and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA.
Ponce Research Institute, Ponce Medical School Foundation, Ponce, Puerto Rico.
Disaster Med Public Health Prep. 2023 Feb 17;17:e315. doi: 10.1017/dmp.2022.285.
To assist communities who suffered from hurricane-inflicted damages, emergency responders may monitor social media messages. We present a case-study using the event of Hurricane Matthew to analyze the results of an imputation method for the location of Twitter users who follow school and school districts in Georgia, USA.
Tweets related to Hurricane Matthew were analyzed by content analysis with latent Dirichlet allocation models and sentiment analysis to identify needs and sentiment changes over time. A hurdle regression model was applied to study the association between retweet frequency and content analysis topics.
Users residing in counties affected by Hurricane Matthew posted tweets related to preparedness ( = 171; 16%), awareness ( = 407; 38%), call-for-action or help ( = 206; 19%), and evacuations ( = 93; 9%), with mostly a negative sentiment during the preparedness and response phase. Tweets posted in the hurricane path during the preparedness and response phase were less likely to be retweeted than those outside the path (adjusted odds ratio: 0.95; 95% confidence interval: 0.75, 1.19).
Social media data can be used to detect and evaluate damages of communities affected by natural disasters and identify users' needs in at-risk areas before the event takes place to aid during the preparedness phases.
为了帮助遭受飓风灾害的社区，应急响应人员可能会监测社交媒体消息。我们通过飓风马修事件的案例研究，分析了一种针对美国佐治亚州跟随学校和学区的推特用户位置的推断方法的结果。
通过潜在狄利克雷分配模型和情感分析对与飓风马修相关的推文进行内容分析和情感分析，以识别需求和随时间变化的情感变化。应用障碍回归模型研究转发频率与内容分析主题之间的关联。
居住在受飓风马修影响的县的用户发布了与准备工作相关的推文（=171；16%）、意识（=407；38%）、行动呼吁或帮助（=206；19%）和疏散（=93；9%），在准备和应对阶段的情绪大多为负面。与路径外的推文相比，准备和应对阶段在飓风路径内发布的推文不太可能被转发（调整后的优势比：0.95；95%置信区间：0.75，1.19）。
社交媒体数据可用于检测和评估受自然灾害影响的社区的损害，并在事件发生前识别高风险地区用户的需求，以便在准备阶段提供援助。
