In the absence of clear, consistent guidelines about the COVID-19 pandemic in the United States, many people use social media to learn about the virus, public health directives, vaccine distribution, and other health information. As people individually sift through a flood of information online, they collectively curate a small set of accounts, known as crowdsourced elites, that receive disproportionate attention for their COVID-19 content. However, these elites are not all created equal: not all accounts have received the same attention during the pandemic, and various demographic and ideological groups have crowdsourced their own elites. Using a mixed-methods approach with a panel of Twitter users in the United States over the first year of the COVID-19 pandemic, we identify COVID-19 crowdsourced elites. We distinguish sustained amplification from episodic amplification and demonstrate that crowdsourced elites vary across demographics with respect to race, geography, and political alignment. Specifically, we show that different subpopulations preferentially amplify elites that are demographically similar to them, and that they crowdsource different types of elite accounts, such as journalists, elected officials, and medical professionals, in different proportions. In light of this variation, we discuss the potential for using the disproportionate online voice of crowdsourced COVID-19 elites to equitably promote public health information and mitigate misinformation across networked publics.

在美国缺乏明确、一致的 COVID-19 大流行指南的情况下，许多人使用社交媒体来了解该病毒、公共卫生指令、疫苗分发和其他健康信息。当人们单独筛选大量在线信息时，他们共同策划了一小部分帐户，称为众包精英，这些帐户因其 COVID-19 内容而受到不成比例的关注。然而，这些精英并非生而平等：在大流行期间并非所有账户都受到了同样的关注，各种人口和意识形态群体都将自己的精英众包。在 COVID-19 大流行的第一年，我们对美国的一组 Twitter 用户使用混合方法，确定了 COVID-19 众包精英。我们区分持续放大和情节放大，并证明众包精英在种族、地理和政治联盟方面因人口统计而异。具体来说，我们表明不同的亚群优先放大与他们在人口统计学上相似的精英，并且他们以不同的比例众包不同类型的精英账户，例如记者、民选官员和医疗专业人员。鉴于这种变化，我们讨论了利用众包 COVID-19 精英不成比例的在线声音来公平地宣传公共卫生信息并减少网络公众中的错误信息的潜力。具体来说，我们表明不同的亚群优先放大与他们在人口统计学上相似的精英，并且他们以不同的比例众包不同类型的精英账户，例如记者、民选官员和医疗专业人员。鉴于这种变化，我们讨论了利用众包 COVID-19 精英不成比例的在线声音来公平地宣传公共卫生信息并减少网络公众中的错误信息的潜力。具体来说，我们表明不同的亚群优先放大与他们在人口统计学上相似的精英，并且他们以不同的比例众包不同类型的精英账户，例如记者、民选官员和医疗专业人员。鉴于这种变化，我们讨论了利用众包 COVID-19 精英不成比例的在线声音来公平地宣传公共卫生信息并减少网络公众中的错误信息的潜力。