RAPID: Capturing Behavioral Response and Perceived Risk to Ebola Using Social Media

2014年9月，当护士Amber Vinson拜访在校园工作的亲戚时，俄亥俄州东北部的居民，特别是肯特州立大学社区的居民，面临着潜在的埃博拉接触，这证实了传染病没有地理界限的事实。像世界各地的许多人一样，学生、教职员工和附近居民对埃博拉的潜在风险做出了反应，他们根据现有信息和感知到的感染风险改变了自己的行为。这项快速反应研究（Rapid）项目将调查这些机制，并提高我们对通过社交媒体传播的信息以及它如何转化为实地感知和行为的理解。如果要利用社交媒体数据加强应急反应和疾病监测系统中的态势感知，这一点至关重要。在这些系统的背景下，社交媒体可以为决策者、应急响应人员和卫生官员提供实时信息，以加快检测、预防、控制和社区行动的过程，从而通过减少流行病、自然灾害或人为灾害等重大风险事件对健康和经济的影响，使整个社会受益。此外，该项目将通过确定信息障碍如何使某些社会群体处于不利地位，帮助解决与灾害有关的社会脆弱性问题。具体来说，这个项目将比较和对比一个封闭系统内的人，如大学或医院，与那些生活在该系统外的人的行为反应。预期的结果将有助于了解如何改善跨社会系统关键信息流动的公平性，以消除这种差距。现在，许多学科都把社交媒体看作是观察社会交流、信仰和行动的一个镜头。然而，很少有研究来验证这些数据的潜力和缺陷，特别是群体之间的社会和地理差异如何影响社交媒体作为数据源的潜在效用。这项变革性的研究将在风险沟通的保护行动决策模型的框架内考虑这两个方面。通过研究信息流与应对重大风险事件的行为变化之间的联系，该项目解决了一个尚未解决的基本问题：来自社交媒体平台Twitter的数据是否代表了实地感知风险和行为反应？该项目通过验证校园内外与埃博拉相关的推文，对近6万人进行了两次及时的调查，以收集风险感知和行为反应数据，从而解决了这个问题。预期的结果不仅将提高对各种情景（包括流行病、自然或人为灾害）的态势感知，而且还将通过验证社交媒体作为适当的数据源来推进围绕每种情景的理论。我们将促进对风险社区跨社会经济、制度、地理和物理-虚拟边界的沟通流的理解。研究结果将通过揭示社交媒体作为数据源的效用、细微差别和局限性，为灾害科学和健康科学的理论发展以及利用社交媒体进行的一般风险沟通提供信息。

Affirming the fact that infectious disease respects no geographic boundary, residents of northeastern Ohio, specifically the Kent State University community, were faced with a potential Ebola exposure during September 2014 when nurse Amber Vinson visited relatives who worked on campus. Students, staff, faculty, and nearby residents responded to the potential risk of Ebola, like many people around the world, by changing their behavior based on available information and their perceived risk of infection. This Grant for Rapid Response Research (RAPID) project will investigate these mechanisms and improve our understanding of information spread through social media and how it translates to on-the-ground perceptions and behaviors. This is vital if social media data are to be used to enhance situational awareness in emergency response and disease surveillance systems. Within the context of these systems, social media may provide real-time information to decision makers, emergency responders, and health officials to speed the process of detection, prevention, control, and community action, thus benefiting society as a whole by reducing the health and economic impact of major risk events including epidemics, natural disasters, or human-caused disasters. In addition, this project will help address disaster related social vulnerability by identifying how information barriers may disadvantage certain social groups. Specifically, this project will compare and contrast the behavior response of those inside a closed system, such as a university or hospital, to those living outside that system. Expected results will help inform how to improve equity in critical information flows across social systems to eliminate such disparities. Multiple disciplines now regard social media as a lens into social communication, belief, and action. Yet, little research has been conducted to validate the potential and pitfalls of these data, in particular, how social and geographic variation between groups impacts the potential utility of social media as a data source. This transformative research will consider both these aspects within the framework of the Protective Action Decision Model for risk communication. By examining the linkages between the flow of information and the change in behavior in response to a major risk event, this project addresses an unresolved fundamental question: are data from the social media platform Twitter representative of on-the-ground perceived risk and behavioral response? This project addresses this question by validating Ebola-related tweets on and around campus with two timely surveys fielded to almost 60,000 people designed to collect risk perception and behavioral response data. Expected results will not only improve situational awareness for various scenarios including epidemics, and natural or human-caused disasters, but also advance theory surrounding each by validating social media as an appropriate data source. We will advance understanding of communication flow across socioeconomic, institutional, geographic, and physical-virtual boundaries for an at-risk community. Outcomes will be used to inform theoretical development across the disaster and health sciences, and general risk communication using social media by revealing the utility, nuance, and limitations of social media as a data source.