Dear All,

You are cordially invited to an onsite academic seminar to be delivered by Dr. Yang Gao on May 24 (Friday). Details could be found below.

Seminar Information

Time and Date: 10:30 am - 12:00 pm, May 24, 2024 (Friday)

Venue: Room 603, Administration Building
Speaker: Dr. Yang Gao (University of Illinois Urbana-Champaign)

Topic: Is Social Bot Socializing? Evidence from a Microblogging Platform

Zoom Access

Link: https://cuhk-edu-cn.zoom.us/j/3985407949?pwd=QnZJMHU3SDUwaFdtWTF6N3RWcGlMdz09

Meeting ID: 398 540 7949
Passcode: 779898

The seminar would be recorded.

About the Speaker

Yang Gao is an Assistant Professor of Business Administration at the Gies College of Business, University of Illinois Urbana-Champaign. He received his Ph.D. from the University of Rochester in 2021. His current research focuses on the management of consumer voices on social media in the era of generative AI. His works have been accepted for publications in journals, including MIS Quarterly, Information Systems Research, Journal of Management Information Systems, and Journal of Operations Management.

Abstract

Leveraging advancements in large language models, social media platforms are deploying sophisticated chatbots, termed social bots, with the potential to stimulate user interaction. However, concerns linger regarding the socializing value of these bots in public settings. We investigate this phenomenon using the data from the launch of CommentRobot on a microblogging platform. Analyzing user interactions with this platform-owned bot, we find that posts receiving bot-generated comments experience increased user engagement, indicating the socializing value of social bots at the post level. Our findings suggest that the quality of bot-generated comments significantly influences user engagement. Moreover, we evaluate the effectiveness of bot targeting strategies and propose improvements to optimize user engagement. Despite the positive impact on post-level engagement, we find no significant effects on users’ future posting behavior, contrary to platform expectations. Theoretically, this study contributes to the literature on social bots and to the “Computers are Social Actors” framework by empirically validating relevant constructs in a novel context. Practically, this study underscores the need for nuanced bot interaction strategies and careful evaluation of their impact on user behavior to maximize engagement in social media platforms.