RAPID: TRACKING AND NETWORK ANALYSIS OF THE SPREAD OF MISINFORMATION REGARDING COVID-19

RAPID：有关 COVID-19 的错误信息传播的跟踪和网络分析

• 批准号: 2031768
• 负责人: Kevin Leicht
• 金额: $ 14.99万
• 依托单位: University of Illinois at Urbana-Champaign
• 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: 2020-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2031768&HistoricalAwards=false
• 关键词: RAPID; TRACKING; NETWORK; ANALYSIS; SPREAD

This project examines the ways that misinformation regarding COVID-19 disseminates through social media and news outlets. The spread of misinformation regarding COVID-19 is part of a larger interest in the communication of accurate and timely scientific information to the public. This project assembles data on English-language news feeds devoted to COVID-19 as well as Facebook, Reddit, twitter, and other social media posts related to COVID-19 to assess the spread of scientific misinformation through social media and the internet with the goal of aiding officials and science advisors in limiting the spread of misinformation as the pandemic unfolds. The ultimate goal is to use machine learning and network analysis tools to provide insight into the locations where misinformation originates and understanding of the mechanisms through which this misinformation spreads.Our project uses the pre-existing infrastructure of the Cline Center and the social media macroscope at the University of Illinois Urbana-Champaign to track the spread of dubious and potentially harmful information on the origins, spread, and treatments for COVID-19. The researchers will use prevailing insights from the Centers for Disease Control to assess what is known currently about COVID-19 and then develop a machine-learning algorithm to detect information on the web and on social media that will be labelled as potentially dubious. The extraction of claims, people, places, and things from these posts will be used to track locations, people, and organizational affiliations of dubious COVID-19 information. The resulting data will be subjected to network analysis techniques that search for structural holes and weak ties through which misinformation spreads with the goal of providing scientists and policy makers with potential information mitigation strategies. The textual and network modelling this project provides will be immediately available through a University of Illinois COVID-19 website, disseminated through press releases and outreach to policy-making community, and integrated into scientific publications that will be published in open-source formats. The long-term implications of our analysis and the ability to identify hot spots and fault-lines in public communication networks and social media sites will be useful for fighting future pandemics as well as other topics that are vital to the health of the Nation.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.

该项目考察了关于COVID-19的错误信息通过社交媒体和新闻媒体传播的方式。传播有关COVID-19的错误信息是向公众传达准确、及时的科学信息这一更大利益的一部分。该项目收集了与COVID-19相关的英文新闻源以及Facebook、Reddit、twitter和其他与COVID-19相关的社交媒体帖子的数据，以评估科学错误信息通过社交媒体和互联网的传播情况，目的是帮助官员和科学顾问在疫情蔓延之际限制错误信息的传播。最终目标是使用机器学习和网络分析工具来洞察错误信息起源的位置，并了解这种错误信息传播的机制。我们的项目利用克莱恩中心现有的基础设施和伊利诺伊大学厄巴纳-香槟分校的社交媒体宏观来追踪有关COVID-19的起源、传播和治疗的可疑和潜在有害信息的传播。研究人员将利用疾病控制中心的主流见解来评估目前对COVID-19的了解，然后开发一种机器学习算法来检测网络和社交媒体上被标记为潜在可疑的信息。从这些帖子中提取索赔、人员、地点和事物将用于跟踪可疑的COVID-19信息的地点、人员和组织从属关系。所得数据将采用网络分析技术，寻找错误信息传播的结构漏洞和弱联系，目的是为科学家和决策者提供潜在的信息缓解战略。本项目提供的文本和网络建模将立即通过伊利诺伊大学COVID-19网站提供，通过新闻稿和向决策界的宣传传播，并整合到将以开源格式出版的科学出版物中。我们的分析的长期影响以及识别公共通信网络和社交媒体网站中的热点和断层的能力将有助于应对未来的流行病以及对国家健康至关重要的其他主题。该奖项反映了美国国家科学基金会的法定使命，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

The Presentation of Self in Virtual Life: Disinformation Warnings and the Spread of Misinformation Regarding COVID-19

虚拟生活中的自我呈现：关于 COVID-19 的虚假信息警告和错误信息的传播

• 发表时间: 2022
• 期刊: RSF: The Russell Sage Journal of the Social Sciences
• 作者: Kevin T. Leicht, Kevin T.;Yun, Joseph;Houston, Brant;Auvil, Loretta;Bracht, Eamon
• 通讯作者: Bracht, Eamon