RAPID: Real time monitoring of information consumption regarding the coronavirus

新冠肺炎疫情突显了准确信息的重要性，它可以帮助公众采取必要措施，确保自己的健康和安全。但社交媒体既包含准确的信息，也包含不准确的信息。这个项目将分析社交媒体如何影响人们在危机延长期间收到的信息的质量。谁会收到什么信息？社交媒体在哪些方面放大或削弱了信息不平等？该项目将建立一个实时监测有关冠状病毒的信息消耗，主要来自Twitter。具体而言，该项目将：(1)建立对有关冠状病毒的信息的实时监测，供州和地方官员使用；(2)评估推特等媒介如何放大/抑制有关社会经济地位的现有信息不平等。该项目将侧重于识别构成健康风险的错误信息(例如，伪装疗法)。该项目将向相关州和地方官员提供有关在其社区中传播的冠状病毒信息的类型和质量的综合信息，从而向政府官员提供干预措施，以打击这种错误信息。更广泛地说，该项目将确定政府官员在其他扩展的危机中可以用来打击错误信息的信息模式，包括那些涉及公共卫生以及其他来源的危机。适当地应对新冠肺炎要求个人拥有关于它是如何传播的以及他们可以做些什么来减轻病毒影响的准确信息。然而，错误信息很普遍，Twitter是准确和不准确信息的主要来源。该项目将利用180万推特账号和选民登记数据的匹配样本。大规模的数据将允许在国家以下级别--州一级和大州的区域内--产生内容共享的合理推断。由于推特数据将与选民登记记录相联系，而且由于选民登记数据包括年龄、性别、种族、党派和地址等信息，因此可以与人口普查地区的信息相联系，该项目将能够评估社会经济状况与信息暴露之间的关系。此外，该项目还将对约2000份匹配数据进行调查，以进一步检查影响人们获得有关冠状病毒的信息质量的因素。该项目的发现将为社会科学中有关信息传播、社会经济不平等、社交媒体使用、网络空间安全和政治差异的理论提供信息。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 COVID-19 pandemic has highlighted the importance of accurate information as a vehicle for helping the public take needed steps to ensure their health and safety. But social media contain both accurate and inaccurate information. This project will analyze how social media affects the quality of information received by people during the extended crisis. Who receives what information? And in what ways do social media amplify or dampen informational inequalities? The project will build a real-time monitor of information consumption regarding the corona virus, drawn largely from Twitter. Specifically, the project will: (1) build a real time monitor of information regarding the corona virus that would be made available to state and local officials; and (2) evaluate how a medium such as Twitter amplifies/dampens existing informational inequalities around socioeconomic status. The project will focus on identification of misinformation (e.g., ersatz cures) that pose health risks. The project will supply aggregate information to relevant state and local officials regarding the type and quality of information regarding corona virus circulating in their communities, thus informing interventions that public officials can make to combat that misinformation. More generally, the project will identify patterns of information that governmental officials can use to combat misinformation during other extended crises, including those with public health as well as other origins.Responding appropriately to COVID-19 requires that individuals have accurate information about how it is spread and what they can do to mitigate virus effects. However, misinformation is prevalent, with Twitter being a major source of both accurate and inaccurate information. This project will utilize a matched sample of 1.8 million Twitter handles and voter registration data. The large scale of the data will permit production of reasonable inferences of content sharing at subnational levels—at the state level, and within regions for large states. Because the Twitter data will be linked to voter registration records, and because voter registration data includes information on age, gender, race, partisanship, and address, thus allowing linkage to census tract information, the project will be able to evaluate the relationship between socioeconomic status and information exposure. Further, the project will augment with a survey of about 2000 of the matched data to further examine the factors that affect the quality of information people receive about the corona virus. Findings from the project will inform theories in the social sciences regarding information diffusion, socioeconomic inequality, social media usage, the security of cyberspace, and political differentiation.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.