演讲人: Raymond LAU副教授

讲座时间: 10月24日（周五）下午14:00-15:30

讲座地点: 信息楼0115教室

讲座内容: Deceptive online product comments have been the subject of discussion in the business press and in the legal circle recently. However, existing methods of deceptive product comment detection cannot scale up with the ever expanding big social media data. Guided by the design science research methodology, one major contribution of our research is the design of novel big data analytics methods for the scalable extraction of near duplicate and diffusion network features from big social media data to enhance deceptive product comment detection. Since very few studies have examined the issue of “veracity” of big data, another important theoretical contribution of our research is the design of a Hadoop-based computational method to automatically assess the “veracity” (e.g., truthfulness) of big social media data. The managerial implication of our research is that organizations can apply our design artifacts to extract more accurate business intelligence from filtered user-contributed comments, and hence to develop timely and effective business strategies. Moreover, management of online social media sites can leverage our design artifacts to improve the hygiene of user-contributed contents archived at their sites. The societal implication of our work is that consumer welfare is better protected due to the filtering of deceptive product comments.

作者介绍

Raymond Y. K. LAU is an Associate Professor in the Department of Information Systems at City University of Hong Kong. Dr. Lau has worked in the ICT industry and the academia for over twenty-five years. He is the author of over 100 refereed international journals and conference papers. His research work has been published in renowned journals such as MIS Quarterly, INFORMS Journal on Computing, ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE Internet Computing, IEEE Computational Intelligence Magazine, Journal of MIS, etc. His research interests include Social Media Analytics, Big Data Stream Analytics, and Information Retrieval. He is the associate editors of ACM Transactions on MIS and the guess associate editor of MIS Quarterly for the special issue of “Big Data”. Dr. Lau is a senior member of the IEEE and the ACM, respectively. He is also a life member of the Hong Kong Computer Society.