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

迅速的;

• 批准号: 2026763
• 负责人: Hank Jenkins-Smith
• 金额: $ 20万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026763&HistoricalAwards=false
• 关键词: RAPID; Information; Implications; Protection; Motivation

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.

目前新冠肺炎病毒的传播和警报提供了一个独特而短暂的机会，可以获得关于公众信念、态度、行为的有意义的时间序列调查数据，以及关于该疾病及其对采取保护行动的影响的各种信息的接收情况。美国国家风险与复原力研究所(NIRR)利用其持续收集的与冠状病毒相关的推特数据(自2020年1月以来收集)，并对全国范围内的公众观点进行一系列月度调查，以测试更广泛的公众对发布在社交媒体上的有关病毒的信息的接受、信任和使用情况。调查将包括关于保护行动行为、对关键行为者的信任、对与疫情相关的风险的看法以及对信息准确性/不准确性的看法。补充的调查和社交媒体数据流将允许跟踪随着时间的推移和疾病传播的信息的传播和渗透，以便将社交媒体上出现的各种叙述与同期调查数据中衡量的信念相匹配。这些时间敏感的数据将允许测试有关社交媒体上信息传播、更广泛的公众信念和行为以及对可能影响传染病传播的保护行为之间的动态关系的假设。这项研究的目标是测量和跟踪推特上有关新冠肺炎疫情的信息在美国公众中的影响力。这项研究整合了两个互补的数据流，系统地考察了信息泡沫和各种形式的信息对应对美国新冠肺炎爆发的保护动机和行动的影响。首先，自2020年1月以来，研究团队通过与推特流媒体API建立连接，收集了推特上所有与新冠肺炎相关的消息。该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、新冠肺炎、SARS-CoV-2、#冠状病毒、#2019_NCoV和#新冠肺炎。从1月27日到2月24日，该团队收集了3100多万条关于该病毒的不同消息。推特上的帖子提供了有关信息网络的演变以及信息的传播和传播的持续流动的数据，但它们没有提供这些因素在多大程度上影响更广泛的公众的保护动机并塑造推动他们的认知(如对感知风险的信任)的信息。其次，该团队收集了全国范围内公众对新冠肺炎了解程度的在线滚动调查，特别关注公众对明年推特上信息的看法。总共有10项全国性调查，每月一次(时间序列横截面)，收集时间定为每周获得250份回复，以提高快速识别信念、看法和相关保护行为变化的能力。这些调查旨在将社交媒体上不断变化的各种信息模式与更广泛的公众对这些信息的接受和信念相结合。这些实验借鉴了推特上各种信息的兴起和传播。这一奖项反映了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。