RAPID/Collaborative Research: Agency COVID-19 Risk Communication on Social Media: Characterizing Drivers of Message Retransmission and Engagement

RAPID/协作研究:社交媒体上的机构 COVID-19 风险沟通:描述消息转发和参与的驱动因素

基本信息

  • 批准号:
    2027475
  • 负责人:
  • 金额:
    $ 9.84万
  • 依托单位:
  • 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:
    2020-05-01 至 2022-04-30
  • 项目状态:
    已结题

项目摘要

Public health and emergency management agencies are on the front lines of informing and educating the public about the science of virus transmission and prevention. In response to a threat such as COVID-19, their mission requires the communication of accurate and credible information to local populations using a variety of media channels. Increasingly, social media is a critical component of their communication toolbox - but using it to rapidly and effectively inform the public in a crowded media environment remains a significant challenge. In prior work on online communication associated with the Zika and Ebola outbreaks, the PIs established that effective messaging depended upon employing a combination of content, style, and structure features - but that the right mix seemed to depend upon properties of the disease event (including the uncertainty and ambiguity of the threat, the nature of the consequences involved, and the need for public information). COVID-19 poses a distinct risk profile, with a disruption potential to the American public and the built environment not seen by any threat within decades. This Rapid Response Research (RAPID) project will identify the key drivers of effective messaging in an emerging pandemic, and strategies for improving effectiveness in social media communication involving COVID-19 by public agencies. The specific focus will be on the outcomes of message retransmission (essential for both high levels of message penetration and ensuring multiple exposures critical for behavioral influence) and engagement (a critical indicator of attention and a driver of trust), both of which are measurable and established as core outcomes in prior studies of effective social media communication. By establishing evidence-based guidance for agencies to effectively warn, inform, and engage the general public during an emerging pandemic, this project will provide critical guidance needed to mount effective interventions that save lives, reduce economic losses, and protect the security of the nation against health threats, in alignment with the broader mission of the NSF.This objective will be pursued through the following core activities: (1) collection of perishable social media data on COVID-19 messaging by public agencies, and public engagement with/retransmission of those messages; (2) content coding of COVID-19 messages, to typologize information that is specific to the present event; (3) characterization of messaging strategies used by public agencies in the evolving COVID-19 response; (4) predictive analysis of message outcomes based on message context, content, style, and structure; and (5) development of evidence-based guidance for effective social media messaging by public agencies in response to this and similar events. This research strategy builds on successful prior work in response to emergent infectious disease threats and in the context of anthropogenic and natural hazard events. The intellectual merit of the research includes: Risk communication messages on social media are real time traces of online in/formal communication shared under conditions of imminent and ongoing threat; Research on communication and messaging dynamics online provides insights into the social amplification of risk, via diffusion of information; and strategies to design effective messages. This project will test the risk communication on social media model in response to a global pandemic by analyzing official communication from state, local, and national public health and emergency management Twitter accounts. The findings from this work will lead to the further development and refinement of the social amplification of risk framework and the risk communication on social media model. The broader impacts of this work most prominently include the accumulation of an evidence base for social media messaging, as noted above. This research will have immediate benefits to organizations and agencies tasked with communicating to at risk populations about emergent infectious disease in the context of the built environment. Our findings will inform the design and dissemination of risk communication messages and will be immediately applicable to public health and safety organizations in the context of COVID-19. Results will be shared via fact sheets, webinars, published papers, and presentations with academic and practitioner audiences.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.
公共卫生和应急管理机构站在向公众宣传和教育病毒传播和预防科学的第一线。为应对COVID-19等威胁,他们的使命要求利用各种媒体渠道向当地民众传达准确可信的信息。社交媒体越来越成为他们沟通工具箱的重要组成部分,但在拥挤的媒体环境中使用它来快速有效地告知公众仍然是一个重大挑战。 在之前与寨卡和埃博拉疫情相关的在线传播工作中,PI确定有效的消息传递取决于采用内容,风格和结构特征的组合-但正确的组合似乎取决于疾病事件的属性(包括威胁的不确定性和模糊性,所涉及的后果的性质以及对公共信息的需求)。 COVID-19构成了一个独特的风险状况,对美国公众和建筑环境的破坏潜力在几十年内没有任何威胁。 这个快速反应研究(RAPID)项目将确定在新出现的大流行病中有效传递信息的关键驱动因素,以及提高公共机构在涉及COVID-19的社交媒体沟通中的有效性的策略。 具体的重点将是消息转发的结果(对于高水平的消息渗透和确保对行为影响至关重要的多重曝光至关重要)和参与(关注的关键指标和信任的驱动因素),这两者都是可衡量的,并在有效的社交媒体传播的先前研究中被确定为核心成果。 通过为各机构制定循证指南,以便在新出现的流行病期间有效地向公众发出警告、提供信息和参与,该项目将提供开展有效干预所需的关键指导,以拯救生命、减少经济损失,并保护国家安全免受健康威胁,与NSF更广泛的使命保持一致。(1)收集公共机构关于COVID-19消息的易逝社交媒体数据,以及公众参与/转发这些消息;(2)COVID-19消息的内容编码,以分类当前事件的特定信息;(3)描述公共机构在不断变化的COVID-19响应中使用的消息策略;(4)基于信息背景、内容、风格和结构对信息结果进行预测分析;(5)为公共机构应对这一事件和类似事件提供有效的社交媒体信息提供循证指南。 这项研究战略建立在成功应对突发传染病威胁以及人为和自然灾害事件的背景下。 该研究的智力价值包括:社交媒体上的风险沟通信息是在迫在眉睫和持续威胁的条件下共享的在线/正式沟通的真实的时间痕迹;在线沟通和消息传递动态研究通过信息传播提供了对风险的社会放大的见解;以及设计有效信息的策略。该项目将通过分析来自州、地方和国家公共卫生和应急管理Twitter账户的官方通信,测试社交媒体模型上的风险沟通,以应对全球流行病。 这项工作的结果将导致进一步发展和完善的社会放大的风险框架和社会媒体上的风险沟通模式。 如上文所述,这项工作的更广泛影响最突出地包括为社交媒体信息传递积累证据基础。 这项研究将对负责在建筑环境中向风险人群传达紧急传染病的组织和机构产生直接的好处。我们的研究结果将为风险沟通信息的设计和传播提供信息,并将立即适用于COVID-19背景下的公共卫生和安全组织。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和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
COVID-19: Retransmission of official communications in an emerging pandemic
  • DOI:
    10.1371/journal.pone.0238491
  • 发表时间:
    2020-09-16
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Sutton, Jeannette;Renshaw, Scott L.;Butts, Carter T.
  • 通讯作者:
    Butts, Carter T.
The First 60 Days: American Public Health Agencies' Social Media Strategies in the Emerging COVID-19 Pandemic
前 60 天:美国公共卫生机构在新出现的 COVID-19 大流行中的社交媒体策略
  • DOI:
    10.1089/hs.2020.0105
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Sutton, Jeannette;Renshaw, Scott L.;Butts, Carter T.
  • 通讯作者:
    Butts, Carter T.
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Carter Butts其他文献

Carter Butts的其他文献

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{{ truncateString('Carter Butts', 18)}}的其他基金

Statistical Models for Dynamic Networks with Endogenous Vertex Migration
具有内生顶点迁移的动态网络的统计模型
  • 批准号:
    1826589
  • 财政年份:
    2018
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Continuing Grant
Collaborative Research: Online Hazard Communication in the Terse Regime: Measurement, Modeling, and Dynamics
合作研究:简洁制度下的在线危险沟通:测量、建模和动态
  • 批准号:
    1536319
  • 财政年份:
    2015
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Standard Grant
Bayesian Methods for Protein Fibrillization: Model Integration and Network Dynamics
蛋白质纤维化的贝叶斯方法:模型集成和网络动力学
  • 批准号:
    1361425
  • 财政年份:
    2014
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Continuing Grant
Doctoral Dissertation Research: Dynamic Network Models for the Scalable Analysis of Networks with Missing or Sampled Joint Edge/Vertex Evolution
博士论文研究:用于缺失或采样联合边/顶点演化的网络可扩展分析的动态网络模型
  • 批准号:
    1260798
  • 财政年份:
    2013
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Standard Grant
Collaborative Research: Informal Online Communication in Extreme Events: Content, Dynamics, and Structure
合作研究:极端事件中的非正式在线交流:内容、动态和结构
  • 批准号:
    1031853
  • 财政年份:
    2010
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Standard Grant
DHB: Large-scale Spatially Embedded Interpersonal Networks: Measurement, Modeling, and Dynamics
DHB:大规模空间嵌入式人际网络:测量、建模和动力学
  • 批准号:
    0827027
  • 财政年份:
    2008
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Standard Grant
SGER: Collaborative Research: Mapping and Analyzing Emergent Multiorganizational networks in the Hurricane Katrina Responsee
SGER:协作研究:绘制和分析卡特里娜飓风响应中的新兴多组织网络
  • 批准号:
    0555125
  • 财政年份:
    2006
  • 资助金额:
    $ 9.84万
  • 项目类别:
    Standard Grant

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