How real-time interaction and sentiment influence online sales? Understanding the role of live streaming danmaku

Live streaming danmaku can reflect both real-time interaction and user sentiment, two key characteristics of live streaming e-commerce. Using a sentiment analysis of live streaming danmaku comments, our study explores the mechanism through which user-user interaction influences live streaming sales. We collect real world data including live streaming danmaku, user stay time, sales from the Douyin live streaming e-commerce platform (the Chinese version of TikTok). Quantifying user-user interaction with BERT model, we then perform a sentiment analysis using the Baidu API. The results of our analysis demonstrate that entertainment-type and information-type user interaction have a significant positive effect on flow, including user stay time, number of danmaku, number of people sending danmaku. Our study also identifies that number of danmaku and number of people sending danmaku play a partial mediating role between user interactions and live streaming sales. Furthermore, we find that user sentiment plays a positive moderating role in the relationships between several flow variables and user purchase behavior. Theoretically, our study proposes a new method to empirically analyze user behavior in live streaming e-commerce. Practically, in light of these findings, we propose several optimization strategies to enhance the interaction functions of live streaming commerce, so as to enhance user experience and stimulate purchase intention.