Carnegie Mellon University

   

Yan Leng and Ying Ding

Tuesday June 23, 2020 4pm-5pm EDT

Zoom Conferencing: Register here to attend

Bio Yan Leng: 

Yan Leng is an incoming Assistant Professor at the McCombs School of Business, the University of Texas at Austin. She obtained the Ph.D. from MIT Media Lab in May 2020. She holds master's degrees in Computer Science and Transportation Engineering, both from MIT. Yan is a network scientist working on social science problems. Her research lies in the intersection of machine learning, network theory, and causal inference. She uses large-scale behavioral data to understand collective human behavior over social networks and builds computational techniques for solving societal and organizational issues. 

Bio Ying Ding:

Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, University of Texas at Austin. Before that, she was a professor and director of graduate studies for data science program at School of Informatics, Computing, and Engineering at Indiana University. She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare. Her current research interests include data-driven science of science, AI in healthcare, Semantic Web, knowledge graph, data science, scholarly communication, and the application of Web technologies.

Talk Title: Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements

Abstract: COVID-19 resulted in an infodemic, which could erode public trust, impede virus containment, and outlive the pandemic itself. Using misinformation identified by the fact-checking platform by Tencent and posts on Weibo, we show that the evolution of misinformation follows an issue-attention cycle, pertaining to topics such as city lockdown, cures, and preventions, and school reopening. Moreover, social media has a complicated relationship with established or legacy media systems. Sometimes they reinforce each other, but in general, social media may have a topic cycle of its own making.