两个空间尺度上Twitter使用与灾害恢复能力的关联:以飓风桑迪为例

IF 2.7 Q1 GEOGRAPHY
Kejin Wang, N. Lam, V. Mihunov
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引用次数: 6

摘要

灾害恢复能力描述了一个社区通过恢复能力建设活动从灾害影响中恢复的能力。社交媒体提供了一种观察人类态度和反应的创新方式,尤其是在灾难期间。然而,之前的大多数社交媒体和灾害研究都是在粗糙的空间尺度上进行的,比如按县进行的。本研究分析了2012年飓风桑迪期间,五个受影响州的县和邮政编码区域级别的Twitter活动。本研究探讨了两个问题:(1)以往研究中发现的县级社会媒体使用差异与抗灾能力差异之间的关系是否仍然存在于邮政编码区域层面?(2)邮政编码区域级分析可以揭示哪些新的信息或模式?结果表明,Twitter使用指数与代表社区恢复力的社会环境变量之间的相关性在县一级仍然成立,但在邮政编码区域水平上较弱。该研究还表明,邮政编码地区拥有主要的交通枢纽和商业活动,或者夜间人口较少,这是影响Twitter使用指数和相关性的主要因素。未来的研究应考虑增加关于土地利用类型和人口动态的数据,以帮助改善社会媒体在抗灾能力分析中的使用。此外,采用多尺度分析方法可以减少分析中的不确定性,更深入地了解Twitter使用与受影响社区的地理和社会经济特征之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Correlating Twitter Use with Disaster Resilience at Two Spatial Scales: A Case Study of Hurricane Sandy
ABSTRACT Disaster resilience describes the ability of a community to bounce back from disaster impacts by resilience building activities. Social media provides an innovative way to observe human attitudes and responses, especially during disasters. However, most previous social media and disasters studies were conducted at a coarse spatial scale such as by county. This study analyzes Twitter activities during Hurricane Sandy in 2012, at the county and the zip code area levels in the five affected states. The study examines two questions: (1) will the relationships between disparities in social media use and disparities in disaster resilience found at the county level in previous studies still hold at the zip code area level? And (2) what new information or patterns can be revealed with the zip code area level analysis? Results show that correlations between Twitter use indices and social-environmental variables representing community resilience found at the county level in previous studies still hold, but they are weaker at the zip code area level. The study also shows that zip code areas that have major transportation hubs and commercial activities or low night-time population are major factors affecting Twitter use indices and hence the correlations. Future research should consider adding data on land use types and population dynamics to help improve social media use for disaster resilience analysis. Furthermore, employing a multiscale analysis approach can reduce uncertainties involved in analysis and obtain a more thorough understanding of the relationships between Twitter use and geographical and socioeconomic characteristics of the affected communities.
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来源期刊
Annals of GIS
Annals of GIS Multiple-
CiteScore
8.30
自引率
2.00%
发文量
31
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