Modeling Rumor Spreading and Debunking Strategies on Social Media During Disasters

社交媒体越来越多地被用作在灾难期间提供及时危机沟通的平台。不幸的是，谣言传播，特别是后来被证明不属实的谣言，已被确定为在灾难期间使用社交媒体的关键问题。例如，在最近的事件中，错误地将特定医院或疏散路线描述为关闭的消息已经流传开来。该项目将通过在社交媒体和灾害管理领域进行数据科学和工程的基础研究，为美国国家科学基金会的大想法“为21世纪的科学与工程利用数据”做出贡献。特别是，该项目将建立目前谣言在灾难期间如何在社交媒体上传播的新模型，以改进未来灾难期间的谣言控制和揭穿谣言。因此，这项科学研究贡献支持了NSF促进科学进步和增进我们国家福利的使命。在这种情况下，好处将是改善危机信息分发和谣言管理做法的洞察力，这将拯救生命，减少经济损失，并减少灾难期间的恐慌、愤怒和困惑。该项目将支持多篇博士论文和硕士论文，并涉及来自不被充分代表的背景的本科生。该项目的研究目标是建模和优化灾难期间社交媒体用户错误信息的决策过程，研究有效的谣言检测策略，并设计和分析灾难期间社交媒体用户的谣言传播和揭穿模型。为了实现研究目标，研究人员将使用社交网络分析、内容分析、决策分析、博弈论、优化和模拟，以：(1)收集和分析社交媒体数据，以识别灾难期间潜在的谣言响应行为及其对谣言传播的影响；(2)通过开发基于谣言文本、评论和传播模式的谣言检测算法，从其他信息中检测谣言；(3)设计和验证单个社交媒体用户的决策模型；以及(4)研究新的谣言传播模型，以研究社交媒体信息传播和揭穿过程的交互作用。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Increasingly, social media has been used as a platform for providing timely crisis communication during a disaster. Unfortunately, rumor spreading, and in particular, rumors that are later proven to be untrue, have been identified as critical issues for the use of social media during disasters. For example, messages that mistakenly describe a particular hospital or evacuation route as closed have circulated during recent events. This project will contribute to the NSF's Big Idea "Harnessing Data for 21st Century Science and Engineering" by conducting fundamental research in data science and engineering in the field of social media and disaster management. In particular, this project will build novel models of how rumors currently spread on social media during disasters to improve rumor control and debunking during future disasters. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare. In this case, the benefits will be insights to improve crisis information distribution and rumor management practices, which will save lives, economic losses, and reduce panic, anger and confusion during disasters. This project will support multiple PhD dissertations and MS theses, and involve undergraduate students from under-represented backgrounds.The research objective of this project is to model and optimize the decision-making processes of misinformed social media users during disasters, to study effective rumor detection strategies, and to design and analyze rumor spreading and debunking models for social media users during disasters. To achieve the research objectives, the researchers will use social network analysis, content analysis, decision analysis, game theory, optimization, and simulation, to: (1) collect and analyze social media data to identify potential rumor responding behaviors during disasters and the impact of their responses on rumor spreading; (2) detect rumors from other information by developing a rumor detection algorithm based on rumor text, comments, and spreading patterns; (3) design and validate a decision making model of individual social media users; and (4) study a new rumor spreading model to study the interaction of spreading and debunking processes of social media information.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.