金融工程研究中心学术报告：Interplay between spreading and debunking processes of online misinformation: A new rumor spreading–debunking model with a case study

报 告 人： 南京审计大学 高庆武 教授 报告时间：2024年7月3日下午15: 00 - 16: 00 报告地点：苏州大学本部览秀楼105学术报告厅   Abstract: In the digital era, massive digital misinformation was ranked first by the World Economic Forum among the top future global risks. As human and financial resources are limited, governments or companies would like to use the optimal level of debunking effort and the most efficient debunking strategy. There exists a rich literature that studies the rumor spreading process on social media. However, a huge gap exists on studying the simultaneous propagation of false rumors and debunking information, and the interplay between them. The spreading of rumors and anti-rumors is a dynamic and reciprocal process. The effective debunking strategy is a potential tool to reduce the loss of massive digital misinformation, this study proposes a novel rumor spreading–debunking model by ordinary differential equation system to explore the interplay mechanism between rumor spreading and debunking processes. We derive and discuss the key factors and parameters that influence the debunking process. Firstly, we consider the spreading pattern of a rumor before Debunkers appear based on the SIR model with its own characteristics of rumor, and obtain a series of results including the final scope of the rumor spreading, the maximal scale of the rumor spreader, the number of Stiflers at any time point, and the popularity level of the rumor. Secondly, with the data from the real world rumor case, the Immigration Rumor during Hurricane Harvey in 2017, we determine the case-specific parameters, and validate our model by comparing the simulated curve with the real data. Our model helps to understand the impact of the rumor on the social media, and predict the future trend. Finally, we use our model to simulate the influence of different debunking strategy, and identify more efficient debunking measures that should be used by the government officials or companies when facing rumor mill under different situations.   报告人简介：高庆武，南京审计大学教授，博士生导师，美国纽约州立大学布法罗分校访问学者，江苏省青蓝工程中青年学术带头人，江苏省青蓝工程优秀青年骨干教师，《美国数学评论》评论员。近年来，主要从事极端保险风险建模及度量、社交媒体谣言传播建模与控制等方面的研究工作；主持科研项目10余项，包括国家级项目3项、省部级项目4项、厅级重大项目1项等；在Mathematical Models and Methods in Applied Science、Applied Mathematics and Computation、Journal of Computational and Applied Mathematics、Journal of Mathematical Analysis and Applications、中国科学等SCI和SSCI期刊上发表论文50余篇，总被引次数889，其中ESI前1%高被引论文1篇。