Does Social Bot Help Socialize? Evidence from a Microblogging Platform

Leveraging advancements in large language models, social media platforms are increasingly 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 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, demonstrating the socializing value of social bots at the post level. Results from an online experiment confirm this finding and reveal that the socializing value stems from both bot identity and high-quality content. Mechanism tests suggest that the quality of bot-generated comments—particularly their attractiveness, relevance, and inclusion of social cues—significantly influences user engagement. Moreover, we evaluate existing bot targeting strategies and propose policy learning-based improvements to optimize engagement. Despite the positive impact on post-level engagement, we find that receiving bot comments primarily encourages future bot-related posts rather than increasing overall user posting activity, contrary to platform expectations. Our findings highlight the need for platforms to refine social bot deployment strategies to maximize user engagement while mitigating unintended consequences.

• 저널Information Systems Research · 37(1) · 416–433
• 토픽Spam and Phishing Detection · Information Systems
• DOI10.1287/isre.2024.1089
• 저자Yang Gao, Maggie Mengqing Zhang, Mikhail Lysyakov