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

RAPID：弱势群体、在线信息和 COVID-19

• 批准号: 2030694
• 负责人: Yonatan Lupu
• 金额: $ 8.54万
• 依托单位: George Washington University
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030694&HistoricalAwards=false
• 关键词: RAPID; Vulnerable; Populations; Online; Information

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.

如果弱势群体获取有关 COVID-19 的不准确信息，他们将面临特别高的风险。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。这些数据显示了 COVID-19 危机首次爆发后，多个在线平台上不准确信息的数量和焦点如何变化，以及信息如何跨平台和不同群体之间传播。该项目研究如何潜在地减轻有关大流行的不准确信息对公共卫生的影响，特别是寻求保护弱势群体中的个人不依赖不准确的信息。该项目收集多个在线平台上在线群组的数据。通过结合人类和机器编码，针对弱势群体的不准确信息在平台上的传播被记录下来。数学模型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智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。

项目成果

How Social Media Machinery Pulled Mainstream Parenting Communities Closer to Extremes and Their Misinformation During Covid-19

Covid-19期间社交媒体机制如何将主流育儿社区推向极端及其错误信息

• DOI: 10.1109/access.2021.3138982
• 发表时间: 2024-09-14
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: N. J. Restrepo;L. Illari;R. Leahy;R. Sear;Y. Lupu;N. Johnson
• 通讯作者: N. Johnson

Online hate network spreads malicious COVID-19 content outside the control of individual social media platforms

在线仇恨网络在个人社交媒体平台的控制之外传播恶意的 COVID-19 内容

• DOI: 10.1038/s41598-021-89467-y
• 发表时间: 2021-06-15
• 期刊: Scientific Reports
• 影响因子: 4.6
• 作者: Velásquez N;Leahy R;Restrepo NJ;Lupu Y;Sear R;Gabriel N;Jha OK;Goldberg B;Johnson NF
• 通讯作者: Johnson NF

Hidden order across online extremist movements can be disrupted by nudging collective chemistry

网络极端主义运动的隐藏秩序可以通过推动集体化学反应来破坏

• DOI: 10.1038/s41598-021-89349-3
• 发表时间: 2021-05-19
• 期刊: Scientific Reports
• 影响因子: 4.6
• 作者: Velásquez N;Manrique P;Sear R;Leahy R;Restrepo NJ;Illari L;Lupu Y;Johnson NF
• 通讯作者: Johnson NF