报告时间：2023年8月5日（星期六）下午15：00-17：00

报告地点：工程管理与智能制造研究中心625会议室

报告人：Wang Weiguang

工作单位：Simon Business School, University of Rochester

举办单位：必赢线路检测中心

报告简介：

The advancement of conversational AI techniques is driving the rise of chatbot applications in various fields. Pioneering business studies have examined the effects of functional chatbots for specific business tasks, such as customer service. This study extends the business literature by focusing on a new type of chatbot, the social chatbot. We develop a GPT-based social chatbot for fitness-related topics and implement it on Twitter. Specifically, this field experiment identifies a strong negative impact of the chatbot’s identity on its ability to engage social media users. We further explore the mechanisms of a reduction in perceived socialization value caused by chatbot identity disclosure by diving into a commonly studied factor, gender matching. The chatbot presents as female, whose perceived socialization value is higher for male social media users. Correspondingly, male users are likely to experience a stronger reduction in perceived socialization value if the account is disclosed as a chatbot. Moreover, we investigate the role of gender cues in the chatbot’s textual replies. While the chatbot is constructed as a female, male cues could potentially present gender inconsistency, which we find to be further detrimental to user engagement after chatbot identity is disclosed.

报告人简介：

Wang Weiguang is a tenure-track assistant professor within the Computers and Information Systems group at the Simon Business School, University of Rochester. His research focuses on Health Information Technologies, primarily concentrating on the development, application, implementation, and impact of machine learning models in healthcare. His research has been published in reputable journals and conferences such as Management Science, JAMA Internal Medicine, Journal of the American Medical Informatics Association, and Journal of Informetrics. He holds a Bachelor’s degree from the University of Science and Technology of China, a Master’s degree from the Institute of Science and Development at the Chinese Academy of Sciences, and a Ph.D. from the University of Maryland.