IBSS-L: Understanding Social and Geographical Disparities in Disaster Resilience Through the Use of Social Media

这一跨学科研究项目将审查在紧急情况管理的四个阶段（缓解、准备、反应和恢复）中是否存在社会和地域差异。研究者将使用多种视角和尺度来解决研究问题，包括在社区、个人和组织尺度上的分析。该项目的研究结果将对地区差异、个人社会网络和行为以及政府/组织政策之间的相互作用提供有价值的见解。该项目将扩大对使用社交媒体是否有助于克服或进一步加深应急管理各阶段的社会和地域差异的认识。该项目将加强对如何对社交媒体数据进行有效挖掘的理解，以产生有用和有效的科学信息，从而通过开发和测试可用于从Twitter等来源挖掘嘈杂和不完美数据的算法，推进社会科学和信息科学研究。从该项目中获得的知识将有助于制定减少差距的战略，开展有效的社会媒体宣传和应急管理外展活动，并提高抗灾能力。本项目所采用的方法将适用于其他地区的其他灾害研究。了解抗灾能力方面的社会和地理差异的来源、模式和后果，对于建立长期抗灾能力、健康和可持续的社区至关重要。传统的弹性分析主要局限于使用定期收集的静态数据。随着“大数据”时代的到来，从社交媒体中提取的实时人类反应数据可以为研究抗灾能力的差异提供新的机会。调查人员将比较2012年发生的飓风艾萨克和飓风桑迪两起事件的推特数据。他们将进行四个相互关联的研究组成部分：(1)开发用于评估和可视化Twitter数据的数据挖掘算法；(2)在整个应急管理周期中，社区（邮政编码）层面的社会媒体和复原力差异分析；(3)对Twitter和非Twitter用户进行在线调查，以了解社交媒体使用对个人心理弹性、社交网络、社会支持和社会差异的影响；(4)居民与政府和非政府组织在每个事件周期中的双向沟通分析。通过对飓风发生前、期间和之后的Twitter数据进行调查，并结合在线调查的分析，研究人员将能够解决一系列核心研究问题：(1)在灾害恢复中使用社交媒体是否存在明显的地理和社会差异？(2)这种差异的来源和后果是什么？(3)这些差异在灾害周期的四个阶段是如何变化的？(4)这些差异如何影响心理弹性？(5)如何使用社交媒体数据来提高弹性？本项目由美国国家科学基金会跨学科行为与社会科学研究（IBSS）竞赛资助。

This interdisciplinary research project will examine whether social and geographical disparities exist during the four phrases of emergency management (mitigation, preparedness, response, and recovery). The investigators will use multiple perspectives and scales to address the research questions, including analysis at the community, individual, and organizational scales. Findings from this project will provide valuable insights into the interplay among regional disparities, individual social networks and behavior, and governmental/organizational policies. This project will expand knowledge of whether social media use may serve to overcome or further deepen the social and geographical disparities in each phase of emergency management. The project will enhance understanding of how to conduct efficient mining of social media data in order to produce useful and valid scientific information, thereby advancing both social science and information science research by developing and testing algorithms that can be used to mine noisy and imperfect data from sources like Twitter. The knowledge gained from this project will help develop strategies to reduce disparities, create effective social media campaigns and emergency management outreach, and promote resilience to disasters. The methods used in this project will be applicable to study other disasters in other regions.Understanding the sources, patterns, and consequences of social and geographical disparities in disaster resilience is critical to building long-term resilient, healthy, and sustainable communities. Traditional resilience analysis has been confined mostly to the use of static data collected at scheduled intervals. With the advent of the "Big Data" era, real-time human response data extracted from social media could provide new opportunities for studying disparities in disaster resilience. The investigators will compare Twitter data from two events, Hurricane Isaac and Hurricane Sandy, both of which occurred in 2012. They will pursue four interrelated research components: (1) development of data-mining algorithms for the evaluation and visualization of Twitter data; (2) analysis of social media and resilience disparities at the community (zip-code) level across the emergency management cycle; (3) an online survey of Twitter and non-Twitter users to understand effects of social media use on individual resilience, social networks, social support, and social disparities; and (4) analysis of bi-directional communication among residents and governmental and non-governmental organizations throughout each event cycle. Through an investigation of the Twitter data before, during, and after the hurricanes coupled with analysis of online surveys, the researchers will be able to address a set of core research questions: (1) Are there distinct geographical and social disparities in the use of social media in disaster resilience? (2) What are the sources and consequences of such disparities? (3) How do these disparities vary across the four phases of the disaster cycle? (4) How do these disparities affect resilience? (5) How can social media data be used to improve resilience? This project is supported through the NSF Interdisciplinary Behavioral and Social Sciences Research (IBSS) competition.