RAPID: Real time monitoring of information consumption regarding the coronavirus

RAPID:实时监控有关冠状病毒的信息消耗

基本信息

  • 批准号:
    2026631
  • 负责人:
  • 金额:
    $ 20万
  • 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:
    2020-04-15 至 2022-09-30
  • 项目状态:
    已结题

项目摘要

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.
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。该项目的研究成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(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

David Lazer其他文献

Categorizing the non-categorical: the challenges of studying gendered phenomena online
对非分类进行分类:在线研究性别现象的挑战
The effects of Facebook and Instagram on the 2020 election: A deactivation experiment
Facebook 和 Instagram 对 2020 年大选的影响:一项停用实验
  • DOI:
    10.1073/pnas.2321584121
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    11.1
  • 作者:
    Hunt Allcott;M. Gentzkow;Winter Mason;Arjun S. Wilkins;Pablo Barberá;Taylor Brown;Juan Carlos Cisneros;Adriana Crespo;Drew Dimmery;Deen Freelon;Sandra González;A. Guess;Young Mie Kim;David Lazer;Neil Malhotra;D. Moehler;Sameer Nair;Houda Nait El Barj;Brendan Nyhan;Ana Carolina Paixao de Queiroz;Jennifer Pan;Jaime Settle;Emily A. Thorson;Rebekah Tromble;Carlos Velasco Rivera;Benjamin Wittenbrink;Magdalena Wojcieszak;Saam Zahedian;Annie Franco;Chad Kiewiet de Jonge;N. Stroud;Joshua A. Tucker
  • 通讯作者:
    Joshua A. Tucker
Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives
利用共同分享来识别主流新闻在推广潜在误导性叙述方面的使用情况
  • DOI:
    10.1038/s41562-025-02223-4
  • 发表时间:
    2025-06-10
  • 期刊:
  • 影响因子:
    15.900
  • 作者:
    Pranav Goel;Jon Green;David Lazer;Philip S. Resnik
  • 通讯作者:
    Philip S. Resnik
A Normative Framework for Assessing the Information Curation Algorithms of the Internet.
评估互联网信息管理算法的规范框架。
DomainDemo: a dataset of domain-sharing activities among different demographic groups on Twitter
域演示:推特上不同人口群体之间的域共享活动的数据集
  • DOI:
    10.1038/s41597-025-05604-6
  • 发表时间:
    2025-07-16
  • 期刊:
  • 影响因子:
    6.900
  • 作者:
    Kai-Cheng Yang;Pranav Goel;Alexi Quintana-Mathé;Luke Horgan;Stefan D. McCabe;Nir Grinberg;Kenneth Joseph;David Lazer
  • 通讯作者:
    David Lazer

David Lazer的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('David Lazer', 18)}}的其他基金

Collaborative Research: State Health, Institutions, and Politics Survey (SHIPS)
合作研究:国家卫生、机构和政治调查 (SHIPS)
  • 批准号:
    2241887
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: U.S. Institutions after COVID-19: Trust, Accountability, and Public Perceptions
合作研究:COVID-19 后的美国机构:信任、责任和公众看法
  • 批准号:
    2116189
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Mid-scale RI-1 (M1:IP): Observatory for Online Human and Platform Behavior
中型 RI-1 (M1:IP):在线人类和平台行为观察站
  • 批准号:
    2131929
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Cooperative Agreement
Collaborative research: Network Dynamics and Corporate Strategies
合作研究:网络动力学和企业战略
  • 批准号:
    1226834
  • 财政年份:
    2012
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research BCC-SBE: Using Archival Resources to Conduct Data-Intensive Internet Research
协作研究 BCC-SBE:利用档案资源进行数据密集型互联网研究
  • 批准号:
    1244730
  • 财政年份:
    2012
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
CDI-Type II: Collaborative Research: Dynamical processes in interdependent techno-social networks
CDI-类型 II:协作研究:相互依赖的技术社交网络中的动态过程
  • 批准号:
    1125095
  • 财政年份:
    2011
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: Connecting to Congress: The Adoption and Use of Web Technologies Among Congressional Offices
协作研究:连接国会:国会办公室对网络技术的采用和使用
  • 批准号:
    1057868
  • 财政年份:
    2010
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Sharing Innovation Across Government Organizations
跨政府组织共享创新
  • 批准号:
    1049595
  • 财政年份:
    2010
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Computational Social Science Workshop at Harvard University's Institute for Quantitative Social Science in January 2010.
2010 年 1 月在哈佛大学定量社会科学研究所举办的计算社会科学研讨会。
  • 批准号:
    0949108
  • 财政年份:
    2009
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Sharing Innovation Across Government Organizations
跨政府组织共享创新
  • 批准号:
    0621242
  • 财政年份:
    2006
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant

相似国自然基金

Immuno-Real Time PCR法精确定量血清MG7抗原及在早期胃癌预警中的价值
  • 批准号:
    30600737
  • 批准年份:
    2006
  • 资助金额:
    22.0 万元
  • 项目类别:
    青年科学基金项目
无色ReAl3(BO3)4(Re=Y,Lu)系列晶体紫外倍频性能与器件研究
  • 批准号:
    60608018
  • 批准年份:
    2006
  • 资助金额:
    28.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

Rapid Acute Leukemia Genomic Profiling with CRISPR enrichment and Real-time long-read sequencing
利用 CRISPR 富集和实时长读长测序进行快速急性白血病基因组分析
  • 批准号:
    10839678
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
Rapid Acute Leukemia Genomic Profiling with CRISPR enrichment and Real-time long-read sequencing
利用 CRISPR 富集和实时长读长测序进行快速急性白血病基因组分析
  • 批准号:
    10651543
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
RAPID: Real-time Forecasting Models for Hospitalizations of Infectious Disease in the USA
RAPID:美国传染病住院实时预测模型
  • 批准号:
    2333435
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Development of a handheld rapid air sensing system to monitor and quantify SARS-CoV-2 in aerosols in real-time
开发手持式快速空气传感系统,实时监测和量化气溶胶中的 SARS-CoV-2
  • 批准号:
    10854070
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
Ultra-Rapid RF-Based Beam Monitor for Real-Time FLASH Beam Control
用于实时闪光光束控制的基于射频的超快速光束监视器
  • 批准号:
    10714368
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
RAPID: ReAl-time Process ModellIng and Diagnostics: Powering Digital Factories
RAPID:实时过程建模和诊断:为数字工厂提供动力
  • 批准号:
    EP/V02860X/1
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Research Grant
RAPID: ReAl-time Process ModellIng and Diagnostics: Powering Digital Factories
RAPID:实时过程建模和诊断:为数字工厂提供动力
  • 批准号:
    EP/V028618/1
  • 财政年份:
    2022
  • 资助金额:
    $ 20万
  • 项目类别:
    Research Grant
Rapid, High-Throughput, and Real-time Assessment of Antibiotic Effectiveness against Pathogenic Biofilms
快速、高通量、实时评估抗生素对致病性生物膜的有效性
  • 批准号:
    2100757
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
RAPID: Real-time Forecasting of COVID-19 risk in the USA
RAPID:美国 COVID-19 风险的实时预测
  • 批准号:
    2108526
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Liquid Biopsy for Rapid Detection and Real Time Monitoring of FGFR-altered Cancers
液体活检用于快速检测和实时监测 FGFR 改变的癌症
  • 批准号:
    10922903
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了