I-Corps: Comprehensive tool to capture spatio-temporal variations in social media health risk communication for COVID-19 and other health risks

这个i-Corps项目的更广泛的影响/商业潜力是开发一个软件平台，该平台可以整合到公共卫生(WHO、CDC)、应急管理(FEMA)和交通(DOT)机构等危机管理系统中，以促进正确信息的传输，并提供向社交媒体提供商通知已识别的错误信息的选项。对于政府机构、政策制定者和应急管理官员来说，有能力在紧迫的时间和资源限制下应对重大危机情景变得越来越重要。更有效地利用社交媒体平台将是迈向这一愿景的关键一步。例如，可以利用这样的沟通平台来更好地沟通新冠肺炎风险。该项目的目标是了解和验证民用或应急管理机构以及联邦、州或市级政府机构对此功能的需求。这项拟议的技术也可能在公共健康风险成为主要问题的其他自然和人为灾难背景下有用。这一i-Corps项目基于开发一种综合工具，以捕获社交媒体健康风险传播(即信息或错误信息)在不同尺度上的时空变化。该项目还将整合数据驱动的方法，以便进行用户友好的预测分析和信息图表，以预测公民的需求和危机应对。拟议的工具将基于最先进的网络科学、社会科学和数据科学的理论和概念。利用Twitter等公开可用的社交媒体平台的应用编程接口(API)，在新型冠状病毒的出现和爆发中收集了大规模的危机沟通数据。这些数据可以作为开发和运营公开可用的新型社交共享平台的能力的概念验证，以自动和被动地检测和控制信息临界点，以促进在流行病和其他社会紧急情况下更好地应对。因此，建议的方法将提供整体支持，以检测重大危机期间社会技术系统中的信息过载、周转、用户反应和响应。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of a software platform that may be integrated into crisis management systems such as public health (WHO, CDC), emergency management (FEMA), and transportation (DOT) agencies to facilitate the transmission of correct information and provide the option to notify social media providers of identified misinformation. It is becoming increasingly important for government agencies, policy makers, and emergency management officials to be capable of addressing major crisis scenarios under acute time and resource constraints. Using social media platforms more efficiently would be a critical step towards this vision. For example, such communications platforms could to be leveraged to better communicate the COVID-19 risk. The goal of this project is to understand and validate the need for this capability in civilian or emergency management agencies, and federal, state, or city level government agencies. The proposed technology also may be useful in other natural and man-made disaster contexts in which public health risks become major concerns.This I-Corps project is based on the development of a comprehensive tool to capture spatio-temporal variations in social media health risk communication (i.e., information or misinformation) at different scales. The project will also integrate data-driven methods for user-friendly predictive analytics and infographics to anticipate citizen needs and crisis responses. The proposed tool will be grounded on state-of-the-art network science, social science, and data science theories and concepts. Using the Application Programming Interface (API) of publicly available social media platforms such as Twitter, large-scale crisis communication data has been collected in the emergence and outbreak of the novel coronavirus. These data may serve as proof-of-concept for the ability to develop and operate publicly-available, novel social sharing platforms to automatically and passively detect and control information tipping points to facilitate better response in pandemics and other societal emergencies. As such, the proposed approach will provide holistic support to detect information overload, turnover, user reaction, and response in socio-technical systems during a major crisis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.