RAPID; Information and Implications for Protection Motivation and Action During the COVID-19 Outbreak

当前COVID-19病毒的传播和警报提供了一个独特而短暂的机会，可以获得有关公众信念、态度、行为和接收有关该疾病及其对采取保护行动的影响的各种信息的有意义的时序调查数据。美国国家风险与复原力研究所（NIRR）利用其正在进行的与冠状病毒相关的推特数据收集（自2020年1月以来收集），并进行了一系列月度全国公众意见调查，以测试更广泛的公众对社交媒体上发布的有关病毒信息的接受、信任和使用情况。调查将包括以下问题：保护性行动行为、对关键行为者的信任、对与疫情有关的风险的看法以及对信息准确性/不准确性的看法。补充调查和社交媒体数据流将允许跟踪信息随时间和疾病传播的传播和渗透，以便与社交媒体上出现的各种叙述以及同期调查数据中测量的信念相匹配。对时间敏感的数据将允许检验关于社交媒体上信息传播、更广泛的公众信仰和行为以及可能影响传染病传播的保护行为的影响之间动态关系的假设。这项研究的目的是衡量和跟踪推特上有关COVID-19大流行的信息对更广泛的美国公众的影响。该研究整合了两种互补的数据流，系统地研究了信息泡沫和各种形式的信息对美国应对COVID-19疫情的保护动机和行动的影响。首先，自2020年1月以来，研究小组通过与推特流媒体API建立连接，收集了推特上与COVID-19相关的所有信息。团队获取包含以下任何关键词的所有帖子和元数据：冠状病毒、COVID-19、SARS-CoV-2、#coronavirus、#2019_nCov和#COVID-19。从1月27日到2月24日，该团队收集了超过3100万条关于该病毒的不同信息。Twitter上的帖子提供了关于信息网络演变以及信息发布和传播的持续数据流，但它们没有提供这些因素在多大程度上影响了更广泛的公众的保护动机，并形成了驱动它们的观念（例如对感知风险的信任）。其次，该团队收集了全国范围内更广泛的公众对COVID-19的理解的在线滚动调查，特别关注未来一年对推特上出现的信息的看法。总共有10项全国性的调查，每月一次（时间序列横截面），收集时间安排为每周获得250份回复，以提高快速识别信念、观念和相关保护行为变化的能力。这些调查的目的是将社交媒体上各种信息的变化模式与更广泛的公众对这些信息的接受和信仰相结合。这些实验是从Twitter上不同类型信息的兴起和传播中得出的结论。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。

The current spread of, and alarm about, the COVID-19 virus provides a unique and ephemeral opportunity to obtain meaningful time-series survey data on public beliefs, attitudes, behaviors, and the receipt of information of various kinds about the disease and its effects on taking protective action. The National Institute for Risk and Resilience (NIRR) utilizes its on-going Twitter data collection associated with coronavirus (collected since January 2020), and undertakes a series of monthly nation-wide surveys on public views to test the broader publics’ receipt of, trust in, and use of information about the virus posted on social media. The surveys will include questions about protective action behavior, trust in key actors, perceptions of risk associated with the outbreak, and perceptions of information accuracy/inaccuracy. The complementary survey and social media data streams will allow tracking the spread and penetration of information over time and as the disease spreads in order to match various narratives as they emerge on social media along with beliefs measured in the contemporaneous survey data. The time sensitive data will permit testing of hypotheses about the dynamic relationships between the spread of information in social media, broader public beliefs and behaviors, and effects on protective behaviors that may influence the spread of contagious diseases.The goal of this study is to measure and track the influence of information about the COVID-19 pandemic on Twitter among members of the broader US public. The study integrates two complementary streams of data to systematically examine the impact of information bubbles and various forms of information on protection motivation and actions in response to the COVID-19 outbreak in the US. First, since January 2020 ,the research team has collected all messages on Twitter that relate to COVID-19, by establishing a connection with the Twitter streaming API. The team obtains all posts and metadata that include any of the following key words: coronavirus, COVID-19, SARS-CoV-2, #coronavirus, #2019_nCov, and #COVID-19. From January 27 to Feb 24, the team collected more than 31 million different messages about the virus. The Twitter posts provide a continuous flow of data about the evolution of information networks and the promulgation and spread of information, but they do not provide information on the extent to which these factors are affecting protective motivations in the broader public and shaping the perceptions that drive them (such as trust in perceived risk). Second, the team collects online rolling nationwide surveys of the broader public’s understanding of COVID-19, with special attention to beliefs about the information that appears on Twitter, over the span of the next year. There are 10 nationwide surveys in all, one each month (time-series cross-sections), with collections timed to obtain 250 responses each week to increase the ability to quickly identify changes in beliefs, perceptions and associated protective behaviors. The surveys are designed to allow pairing the changing pattern of information of various sorts on social media with the receipt and belief of that information among the broader public. The experiments draw from the rise and spread of different kinds of information on Twitter.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.