NSF Convergence Accelerator Track F: Course Correct: Precision Guidance Against Misinformation

NSF 融合加速器轨道 F：路线正确：针对错误信息的精确指导

• 批准号: 2230692
• 负责人: Michael Wagner
• 金额: $ 500万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230692&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Course

The NSF Convergence Accelerator supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future. This project, Course Correct—Precision Guidance Against Misinformation, is a flexible and dynamic digital dashboard that will help end users such as journalists to (1) identify trending misinformation networks on social media platforms like Twitter, Facebook, and TikTok, (2) strategically correct misinformation within the flow of where it is most prevalent online and (3) test the effectiveness of corrections in real time. In Phase II, Course Correct will partner with local, state, national, and international news and fact-checking organizations to test how well the Course Correct digital dashboard helps journalists detect misinformation, correct misinformation, share message interventions containing the verifiable truth into misinformation networks, and verifying the success of the corrections. This project aims to (1) extend our use of computational means to detect misinformation, using multimodal signal detection of linguistic and visual features surrounding issues such as vaccine hesitancy and electoral skepticism, coupled with network analytic methods to pinpoint key misinformation diffusers and consumers; (2) continue developing A/B-tested correction strategies against misinformation, such as observational correction, using ad promotion infrastructure and randomized message delivery to optimize efficacy for countering misinformation; (3) disseminate and evaluate the effectiveness of evidence-based corrections using various scalable intervention techniques available through social media platforms by conducting small, randomized control trials within affected networks, focusing on diffusers, not producers of misinformation and whether our intervention system can reduce the misinformation uptake and sharing within their social media networks; and (4) scale Course Correct into local, national, and international newsrooms, guided by dozens of interviews and ongoing collaborations with journalists, as well as tech developers and software engineers. By the end of Phase II, Course Correct intends to have further developed the digital dashboard in ways that could ultimately be adopted by other end users such as public health organizations, election administration officials, and commercial outlets.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.

NSF融合加速器支持以使用为灵感，以团队为基础，多学科的努力，以应对国家重要性的挑战，并将在不久的将来为社会提供有价值的成果。该项目名为“针对错误信息的课程正确性-精确性指导”，是一个灵活、动态的数字仪表板，将帮助记者等最终用户（1）识别Twitter、Facebook和TikTok等社交媒体平台上的热门错误信息网络，（2）在最流行的网络流中对错误信息进行战略性纠正，（3）在真实的时间内测试纠正的有效性。在第二阶段，Course Correct将与地方、州、国家和国际新闻和事实核查组织合作，测试Course Correct数字仪表板如何帮助记者发现错误信息，纠正错误信息，将包含可验证真相的消息干预措施分享到错误信息网络，并验证纠正的成功。该项目旨在（1）扩大我们使用计算手段来检测错误信息，使用多模态信号检测围绕疫苗犹豫和选举怀疑等问题的语言和视觉特征，结合网络分析方法来确定关键的错误信息传播者和消费者;（2）继续开发针对错误信息的A/B测试纠正策略，如观察纠正，使用广告促销基础设施和随机消息传递来优化对抗错误信息的功效;（3）通过在受影响的网络中进行小型随机对照试验，利用社交媒体平台提供的各种可扩展干预技术，传播和评估循证矫正的有效性，关注传播者，而不是错误信息的制造者，以及我们的干预系统是否可以减少他们的社交媒体网络中的错误信息吸收和共享;（4）通过数十次采访和与记者以及技术开发人员和软件工程师的持续合作，将Course Correct扩展到地方，国家和国际新闻编辑室。到第二阶段结束时，Course Correct计划进一步开发数字仪表板，最终可被其他最终用户（如公共卫生组织、选举管理官员和商业机构）采用。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。