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Paper Number
1360
Paper Type
Complete
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 uncover heterogeneous effects of bot comments across different post- and user-level characteristics. Despite the positive impact on post-level engagement, we find no significant effects on users’ future posting behavior, contrary to platform expectations. This study contributes to the literature on social bots and underscores the need for nuanced bot interaction strategies in social media.
Recommended Citation
Gao, Yang; Zhang, Maggie Mengqing; and Lysyakov, Mikhail, "Is Social Bot Socializing? Evidence from a Microblogging Platform" (2024). ICIS 2024 Proceedings. 12.
https://aisel.aisnet.org/icis2024/socmedia_digcollab/socmedia_digcollab/12
Is Social Bot Socializing? Evidence from a Microblogging Platform
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 uncover heterogeneous effects of bot comments across different post- and user-level characteristics. Despite the positive impact on post-level engagement, we find no significant effects on users’ future posting behavior, contrary to platform expectations. This study contributes to the literature on social bots and underscores the need for nuanced bot interaction strategies in social media.
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