CAREER: Unraveling Online Disinformation Trajectories: Applying and Translating a Mixed-Method Approach to Identify, Understand and Communicate Information Provenance

职业：揭开在线虚假信息的轨迹：应用和转化混合方法来识别、理解和交流信息来源

• 批准号: 1749815
• 负责人: Kate Starbird
• 金额: $ 55万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1749815&HistoricalAwards=false
• 关键词: CAREER; Unraveling; Online; Disinformation; Trajectories

This project will improve our understanding of the spread of disinformation in online environments. It will contribute to the field of human-computer interaction in the areas of social computing, crisis informatics, and human centered data science. Conceptually, it explores relationships between technology, structure, and human action - applying the lens of structuration theory towards understanding how technological affordances shape online action, how online actions shape the underlying structure of the information space, and how those integrated structures shape information trajectories. Methodologically, it enables further development, articulation and evaluation of an iterative, mixed method approach for interpretative analysis of "big" social data. Finally, it aims to leverage these empirical, conceptual and methodological contributions towards the development of innovative solutions for tracking disinformation trajectories. The online spread of disinformation is a societal problem at the intersection of online systems and human behavior. This research program aims to enhance our understanding of how and why disinformation spreads and to develop tools and methods that people, including humanitarian responders and everyday analysts, can use to detect, understand, and communicate its spread. The research has three specific, interrelated objectives: (1) to better understand the generation, evolution, and propagation of disinformation; (2) to extend, support, and articulate an evolving methodological approach for analyzing "big" social media data for use in identifying and communicating "information provenance" related to disinformation flows; (3) to adapt and transfer the tools and methods of this approach for use by diverse users for identification of disinformation and communication of its origins and trajectories. More broadly, it will contribute to the advancement of science through enhanced understandings and conceptualization of the relationships between technological affordances, social network structure, human behavior, and intentional strategies of deception. The program includes an education plan that supports PhD student training and recruits diverse undergraduate students into research through multiple mechanisms, including for-credit research groups and an academic bridge program.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.

该项目将增进我们对网络环境中虚假信息传播的理解。它将为社会计算、危机信息学和以人为中心的数据科学领域的人机交互领域做出贡献。从概念上讲，它探讨了技术、结构和人类行为之间的关系——应用结构理论的视角来理解技术可供性如何塑造在线行为，在线行为如何塑造信息空间的底层结构，以及这些集成结构如何塑造信息轨迹。在方法论上，它能够进一步开发、阐明和评估用于“大”社会数据解释分析的迭代混合方法。最后，它的目标是利用这些经验、概念和方法论的贡献来开发跟踪虚假信息轨迹的创新解决方案。虚假信息的在线传播是在线系统和人类行为交叉点的一个社会问题。该研究项目旨在加深我们对虚假信息传播方式和原因的理解，并开发人们（包括人道主义救援人员和日常分析师）可以用来检测、理解和传达虚假信息传播的工具和方法。该研究有三个具体的、相互关联的目标：（1）更好地了解虚假信息的产生、演变和传播； (2) 扩展、支持和阐明一种不断发展的方法论，用于分析“大”社交媒体数据，用于识别和传达与虚假信息流相关的“信息来源”； (3) 调整和转移该方法的工具和方法，供不同用户使用，以识别虚假信息并传达其起源和轨迹。更广泛地说，它将通过增强对技术可供性、社交网络结构、人类行为和故意欺骗策略之间关系的理解和概念化，为科学的进步做出贡献。该计划包括一项教育计划，支持博士生培训，并通过多种机制招募不同的本科生进行研究，包括学分研究小组和学术桥梁计划。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

Repeat Spreaders and Election Delegitimization: A Comprehensive Dataset of Misinformation Tweets from the 2020 U.S. Election

重复传播者和选举非法化：2020 年美国大选错误信息推文的综合数据集

• DOI: 10.51685/jqd.2022.013
• 发表时间: 2022
• 期刊: Journal of Quantitative Description: Digital Media
• 作者: Kennedy, Ian;Wack, Morgan;Beers, Andrew;Schafer, Joseph S.;Garcia-Camargo, Isabella;Spiro, Emma S.;Starbird, Kate
• 通讯作者: Starbird, Kate

Mobilizing Manufactured Reality: How Participatory Disinformation Shaped Deep Stories to Catalyze Action during the 2020 U.S. Presidential Election

动员人造现实：参与性虚假信息如何塑造深层故事以催化 2020 年美国总统选举期间的行动

• DOI: 10.1145/3579616
• 发表时间: 2023
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Prochaska, Stephen;Duskin, Kayla;Kharazian, Zarine;Minow, Carly;Blucker, Stephanie;Venuto, Sylvie;West, Jevin D.;Starbird, Kate
• 通讯作者: Starbird, Kate

Spotlight Tweets: A Lens for Exploring Attention Dynamics within Online Sensemaking During Crisis Events

聚光灯推文：探索危机事件期间在线意义建构中注意力动态的镜头

• DOI: 10.1145/3577213
• 发表时间: 2023
• 期刊: ACM Transactions on Social Computing
• 作者: Zhou, Kaitlyn;Wilson, Tom;Starbird, Kate;Spiro, Emma S.
• 通讯作者: Spiro, Emma S.

Influence and Improvisation: Participatory Disinformation during the 2020 US Election

影响力与即兴发挥：2020 年美国大选期间的参与性虚假信息

• DOI: 10.1177/20563051231177943
• 发表时间: 2023
• 期刊: Social Media + Society
• 影响因子: 5.2
• 作者: Starbird, Kate;DiResta, Renée;DeButts, Matt
• 通讯作者: DeButts, Matt

On the Misinformation Beat: Understanding the Work of Investigative Journalists Reporting on Problematic Information Online

关于错误信息的节拍：了解调查记者在线报道问题信息的工作

• DOI: 10.1145/3415204
• 发表时间: 2020
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: McClure Haughey, Melinda;Muralikumar, Meena Devii;Wood, Cameron A.;Starbird, Kate
• 通讯作者: Starbird, Kate