Examining the impact of the platform-based generative AI usage on users' activity on a knowledge-sharing platform 

Yuan Dong, Guohou Shan. 

Abstract: Generative AI has been growing fast. It gradually changes users' behavior of seeking knowledge. Witnessing the impact, knowledge platforms have gradually adopted various strategies to leverage generative AI tools to improve their users' engagement. However, it is unknown whether platform-based generative AI adoption affects users' activity in terms of answering and questioning behavior on the knowledge-sharing platform. We address this research question by leveraging a natural experiment on one of the largest knowledge-sharing platforms, with a difference-in-differences (DID) approach. Our research aims to contribute to the literature around both knowledge sharing and generative AI adoption by understanding whether and how platform-initiated generative AI usage affects users' activity. In addition, our research findings will help managers and owners of knowledge-sharing platforms leverage generative AI tools to boost users' engagement and improve platform growth.