RAPID: Real time monitoring of information consumption regarding the coronavirus

COVID-19疫情凸显了准确信息作为帮助公众采取必要措施以确保其健康和安全的工具的重要性。 但社交媒体包含准确和不准确的信息。该项目将分析社交媒体如何影响人们在长期危机期间收到的信息质量。谁接收什么信息？社交媒体以何种方式放大或抑制信息不平等？该项目将建立一个关于冠状病毒的信息消费的实时监控器，主要来自Twitter。具体而言，该项目将：（1）建立一个真实的实时监测有关冠状病毒的信息，将提供给州和地方官员;（2）评估Twitter等媒体如何放大/抑制现有的社会经济地位信息不平等。 该项目将侧重于查明错误信息（例如，危险的治疗），造成健康风险。该项目将向相关州和地方官员提供有关其社区传播的冠状病毒信息的类型和质量的汇总信息，从而为公职人员可以采取的干预措施提供信息，以打击这种错误信息。更广泛地说，该项目将确定政府官员可以用来在其他长期危机中打击错误信息的信息模式，包括那些与公共卫生以及其他来源有关的危机。适当应对COVID-19需要个人掌握有关其传播方式的准确信息，以及他们可以做些什么来减轻病毒影响。 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180万个Twitter用户名和选民登记数据的匹配样本。大规模的数据将允许生产合理的推断内容共享在国家以下的水平，在国家一级，并在大州的区域内。由于Twitter数据将与选民登记记录相关联，而且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区信息相关联，因此该项目将能够评估社会经济地位与信息披露之间的关系。此外，该项目还将对大约2000个匹配数据进行调查，以进一步研究影响人们获得冠状病毒信息质量的因素。该项目的研究结果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分化的理论提供信息。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值进行评估而被认为值得支持。和更广泛的影响审查标准。

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.