A Graph-based Approach for Detecting Critical Infrastructure Disruptions on Social Media in Disasters
A Graph-based Approach for Detecting Critical Infrastructure Disruptions on Social Media in Disasters
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DOI：
10.24251/hicss.2019.239
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发表时间：
2019-01
期刊：
影响因子：
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通讯作者：
Chao Fan;A. Mostafavi;Wenlin Yao;Ruihong Huang
中科院分区：
文献类型：
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作者：
Chao Fan;A. Mostafavi;Wenlin Yao;Ruihong Huang
本文的目的是提出并测试一种基于图的方法，用于检测灾难中社交媒体数据中的关键基础设施中断。了解关键基础设施的状况和破坏性事件对于有效应对灾害和社区恢复至关重要。最近的研究强调了社会媒体数据在灾害期间对情况了解的潜力。然而，社会感知在检测关键基础设施的中断的应用是有限的，因为现有的方法不能提供完整的和明确的情况下，关键基础设施的信息。因此，为了解决这一方法上的差距，我们开发了一种基于图的方法，包括数据过滤，突发时间帧检测，内容相似性和图分析。以2017年休斯顿飓风哈维为例，说明了所提出方法的应用。调查结果突出了灾害中发生的关键基础设施事件的时间模式，包括破坏性事件及其对社区的不利影响。研究结果还为更好地理解灾害中关键基础设施的相互依赖性提供了见解。从实践的角度来看，拟议的方法研究可以提高社区成员、第一反应者和决策者发现和应对灾害中基础设施中断的能力。
The objective of this paper is to propose and test a graph-based approach for detection of critical infrastructure disruptions in social media data in disasters. Understanding the situation and disruptive events of critical infrastructure is essential to effective disaster response and recovery of communities. The potential of social media data for situation awareness during disasters has been highlighted in recent studies. However, the application of social sensing in detecting disruptions of critical infrastructure is limited because existing approaches cannot provide complete and nonambiguous situational information about critical infrastructure. Therefore, to address this methodological gap, we developed a graph-based approach including data filtering, burst time-frame detection, content similarity and graph analysis. A case study of Hurricane Harvey in 2017 in Houston was conducted to illustrate the application of the proposed approach. The findings highlighted the temporal patterns of critical infrastructure events that occurred in disasters including disruptive events and their adverse impacts on communities. The findings also provided insights for better understanding critical infrastructure interdependencies in disasters. From the practical perspective, the proposed methodology study can improve the ability of community members, first responders and decision makers to detect and respond to infrastructure disruptions in disasters.