A method to characterize the social cascading damage processes of disasters using media information
A method to characterize the social cascading damage processes of disasters using media information
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DOI：
10.1007/s11069-021-04581-4
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发表时间：
2021-02
期刊：
影响因子：
3.7
通讯作者：
H. Noguchi;Takuma Nishizawa;M. Fuse
中科院分区：
文献类型：
--
作者：
H. Noguchi;Takuma Nishizawa;M. Fuse
不断发展的媒体信息是表征自然灾害后社会级联损害过程的关键数据来源。然而，媒体信息往往包括大样本量，但低信息密度。考虑到这些特性，本研究的目的是开发一种基于媒体的信息表征社会级联损伤过程的新方法。在开发该方法的过程中，构建了一个网络理论框架，以系统地整合媒体信息及其表征。该方法包括两个分析部分：系统地输入媒体信息的灾害损害网络和使用度中心性概念的网络分析。开发的方法将报纸文章作为媒体信息来源，应用于2018年日本西部破纪录的暴雨灾害。该研究确定了关键的灾难事件及其关系。这个案例研究表明，我们的方法将为决策者提供潜在的基础信息，以支持灾害管理，从而使他们受益。
Constantly advancing media information is a key data source to characterize the social cascading damage processes following natural hazards. However, media information tends to include a large sample size but low information density. In consideration of these properties, the aim of this study is to develop a new method for media-based information characterizing social cascading damage processes. In developing the method, a network theory framework was constructed to systematically integrate media information and its characterization. The method has two analytical components: a disaster damage network systematically inputting media information and network analysis using the concept of degree centrality. The developed method was applied to the record-breaking 2018 heavy rain disaster in western Japan, employing newspaper articles as media information sources. The study identified the critical disaster events and their relationships. This case study demonstrates that our method will benefit policymakers by providing them with potential fundamental information to support disaster management.