RAPID: Vulnerable Populations, Online Information, and COVID-19

RAPID:弱势群体、在线信息和 COVID-19

基本信息

  • 批准号:
    2030694
  • 负责人:
  • 金额:
    $ 8.54万
  • 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:
    2020-07-01 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

Vulnerable populations are especially at-risk if they consume inaccurate information about COVID-19. This project generates data and analyses that can be used to better limit and control the spread of inaccurate information about COVID-19 that targets vulnerable populations. The data shows how the amount and focus of inaccurate information on several online platforms changed after the initial outbreak of the COVID-19 crisis, and how the information moved across platforms and among different groups. The project examines how to potentially mitigate the effects of inaccurate information about the pandemic on public health, and in particular seeks to protect individuals in vulnerable groups from relying on inaccurate information. This project collects data on online groups across multiple online platforms. Using a combination of human- and machine-coding, the diffusion of inaccurate information targeted to vulnerable groups across platforms is documented. Mathematical modeling is used to understand the dynamics of how inaccurate information diffuses across networks, as well as the relative potential effectiveness of strategies to reduce its spread.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.
如果弱势群体消费关于COVID-19的不准确信息,他们面临的风险尤其大。该项目生成的数据和分析可用于更好地限制和控制针对弱势群体的有关COVID-19的不准确信息的传播。数据显示了COVID-19危机最初爆发后,几个在线平台上不准确信息的数量和重点如何变化,以及信息如何在平台之间和不同群体之间移动。该项目审查如何可能减轻关于这一流行病的不准确信息对公共卫生的影响,特别是设法保护弱势群体中的个人,使其不依赖不准确的信息。该项目收集了多个在线平台上在线群体的数据。使用人工和机器编码相结合的方式,记录了针对弱势群体的不准确信息在平台上的传播情况。数学建模用于了解不准确信息如何在网络中传播的动态,以及减少其传播的策略的相对潜在有效性。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)
How Social Media Machinery Pulled Mainstream Parenting Communities Closer to Extremes and Their Misinformation During Covid-19
  • DOI:
    10.1109/access.2021.3138982
  • 发表时间:
    2022-01-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Restrepo, Nicholas J.;Illari, Lucia;Johnson, Neil F.
  • 通讯作者:
    Johnson, Neil F.
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Yonatan Lupu其他文献

Inferring mechanisms for global constitutional progress
推断全球宪法进步的机制
  • DOI:
    10.1038/s41562-018-0382-8
  • 发表时间:
    2018-08-06
  • 期刊:
  • 影响因子:
    15.900
  • 作者:
    Alex Rutherford;Yonatan Lupu;Manuel Cebrian;Iyad Rahwan;Brad L. LeVeck;Manuel Garcia-Herranz
  • 通讯作者:
    Manuel Garcia-Herranz

Yonatan Lupu的其他文献

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{{ truncateString('Yonatan Lupu', 18)}}的其他基金

EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Deplatforming and Online Hate Speech Across the Social Media Ecology
EAGER:DCL:SaTC:实现跨学科合作:社交媒体生态中的去平台化和在线仇恨言论
  • 批准号:
    2210023
  • 财政年份:
    2022
  • 资助金额:
    $ 8.54万
  • 项目类别:
    Standard Grant
Collaborative Research: Violence, Non-Violence and the Effects of Human Rights Laws
合作研究:暴力、非暴力和人权法的影响
  • 批准号:
    1627079
  • 财政年份:
    2016
  • 资助金额:
    $ 8.54万
  • 项目类别:
    Standard Grant

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