RAPID: Dynamic Interactions between Human and Information in Complex Online Environments Responding to SARS-COV-2

该快速反应研究（Rapid）项目有助于了解美国大规模流行病爆发（COVID-19）期间在线环境中的风险、危机沟通和行为传染的基本知识。该项目通过定量展示社交媒体在美国COVID-19大流行应对期间信息传播中的复杂作用，提高了卫生和应对机构如何更好地确保可信信息在社交媒体中占主导地位的知识。调查结果将有助于了解如何减少不当行为（即不保持身体距离）的风险以及由于错误或虚假信息造成的可预防死亡，所开发的工具将能够及时跟踪准确和不准确信息的传播。这些发现将支持NSF促进科学进步和促进国家健康和福祉的使命，特别是在重大健康危机的关键任务环境中。该研究项目研究在网络环境（即Twitter）中传播COVID-19的信息和人类反应动态。该研究确定了关键影响因素和错误信息来源，并研究了不同信息类别随时间的共同进化。结果将有助于人口卫生机构和利益攸关方更好地了解如何战略性地利用可信信息压制错误信息并减轻其不利后果。此外，该项目揭示了不协调的信息如何破坏社区响应目标。该研究通过考察公共卫生机构、其他政府利益相关者和公众在动态信息流网络中的社交媒体活动、情绪和关注主题，解开了公共卫生机构、其他政府利益相关者和公众之间沟通的互动影响。研究结果将为今后的病毒传播和预防风险沟通战略提供信息。研究人员使用系统动态建模来研究COVID-19特定通信的参考模式。这些技术评估关于流行病控制沟通的可信信息和错误信息的时间轨迹，进而为未来复杂的大规模伤亡事件和灾难性健康事件（如致命性流行病和全球大流行病）风险沟通的战略协调提供信息。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Rapid Response Research (RAPID) project contributes to fundamental knowledge of risk, crisis communication and behavioral contagion in online environments during a large-scale pandemic outbreak (COVID-19) in the U.S. This project advances knowledge of how health and response agencies can better ensure credible information predominates in social media by quantitatively demonstrating the complex roles of social media in information diffusion during the U.S. COVID-19 pandemic response. Findings will aid in understanding how to reduce the risk of inappropriate behaviors (i.e. not practicing physical distancing) and preventable deaths due to mis- or disinformation and tools developed will enable time-critical tracking of the spreading of accurate and inaccurate information. These findings will support NSF's mission to promote the progress of science and to advance national health and well-being, especially during mission-critical circumstances of major health crises.The research project studies information and human response dynamics in communicating COVID-19 in an online environment, i.e. Twitter. The research identifies key influencers and misinformation sources and examines co-evolution in different information categories over time. Results will help population health agencies and stakeholders better understand how the strategic leveraging of credible information suppresses misinformation and can moderate its adverse consequences. Further, the project reveals how incongruous information may undermine community response goals. The research disentangles the interactive influences of communications between public health agencies, other governmental stakeholders, and the public by examining their social media activities, sentiments, and concerned topics in dynamic information flow networks. Findings will inform future risk communication strategies of virus transmission and prevention. The researchers use system dynamic modeling to investigate reference modes of COVID-19 specific communication. These techniques assess temporal trajectories of credible information and misinformation regarding epidemic-control communication, which in turn, informs the strategic coordination of future risk communication of complex mass casualty events and catastrophic health events such as virulent epidemics and global pandemics.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.