Minimum data set.

The objective of this study is to examine the mechanisms that influence tourists’ intentions to travel in the context of live streaming. The utilization of text mining techniques in this research endeavor has yielded two critical dimensions, namely, the characteristics of live streamers and the attributes of live streaming content, as discerned from user comments. The present study proposes a model grounded in the Stimulus-Organism-Response (SOR) theoretical framework. Subsequently, a series of questionnaires were disseminated through various digital platforms, including WeChat, QQ, and TikTok. This endeavor yielded a total of 511 valid responses from audiences within China’s travel live streaming sector. Subsequently, structural equation modeling (SEM) was employed to analyze the data. The findings indicate that live streamer characteristics (e.g., professionalism, image, charm), live streaming content characteristics (e.g., tourist destination information), perceived emotional value, and perceived utilitarian value can directly influence tourists’ intention to travel on the spot. Furthermore, live streamer characteristics and live streaming content characteristics directly impact perceived emotional value and perceived utilitarian value, and indirectly influence travel intention through double intermediaries.