報(bào)告時(shí)間：2022年5月23日（星期一）9:00-10:30
報(bào)告平臺(tái)：騰訊會(huì)議 ID: 319 221 770、密碼：1515
報(bào) 告 人：魏煊 博士
工作單位：上海交通大學(xué)
舉辦單位：管理學(xué)院
報(bào)告簡(jiǎn)介：
Although the past decade has witnessed the great rise of AI, the current AI approaches have systematic weaknesses and blind spots in many applications. There is strong motivation to develop hybrid collective intelligence systems which tap into the complementary strengths of humans and machines and the power of collective intelligence. This report is going to introduce hybrid collective intelligence and show how to apply it in the task of false news detection. We propose combining two types of scalable crowd judgments with machine intelligence to tackle the false news crisis. Specifically, we design a hybrid framework called CAND, which first extracts relevant human and machine judgments from data sources including news features and scalable crowd intelligence. The extracted information is then aggregated by an unsupervised Bayesian aggregation model. Evaluation based on Weibo and Twitter datasets demonstrates the effectiveness of such hybrid approach.
報(bào)告人簡(jiǎn)介：
Xuan Wei is an assistant professor in the Department of Information, Technology and Innovation, Antai College of Economics and Management, Shanghai Jiao Tong University. He received his B.S. degree from the Shanghai Jiao Tong University in 2014 and his Ph.D. degree in management information systems at the University of Arizona in 2020. His research interests include crowd intelligence and crowdsourcing, social media analytics, statistical machine learning, probabilistic modeling and interference, and deep learning. His work has been published in journals such as MIS Quarterly, INFORMS Journal on Computing, Nature Human Behaviour, and many others.
