时 间：3月30 日下午2点30分

腾讯会议：562438312

主 题：Hybrid Collective Intelligence and its Applications in False News Detection

内 容：Although the past decade has witnessed the great rise of Artificial Intelligence (AI), it is still broadly acknowledged that 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.

The explosive spread of false news on social media has severely affected many areas such as news ecosystems, politics, economics, and public trust, especially amid the COVID-19 infodemic. We propose combining these 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 and the superior performance of the proposed framework in comparison with the benchmark methods.

主讲人简介：魏煊，上海交通大学安泰经济与管理学院助理教授，博士毕业于美国亚利桑那大学Eller商学院，主要研究领域为人工智能、混合智慧与人智交互、群体智慧、社交媒体分析等。入选两项省部级人才计划，主持国家自然科学基金青年项目1项和上海市课题1项。参与国家自然科学基金创新研究群体1项、重大项目1项、重点项目1项、面上项目4项，青年基金1项。发表8篇高水平国际期刊论文，包括UTD 24列表的MIS Quarterly, INFORMS Journal on Computing, 以及Nature子刊Nature Human Behaviour, Decision Support Systems, Information & Management等，并曾在INFORMS等多个国际会议上获得最佳论文奖。

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