Research on the impact of streamers' linguistic emotional valence on live streaming performance in live streaming shopping environments

As an emerging retail model, live streaming shopping involves real-time interactions between streamers and viewers, and among the viewers themselves. In live streaming interactions, the comments posted by the viewers reflect their emotional states, which may have been influenced by the streamers' emotional expression. This study utilized the S-O-R model and emotional contagion theory as its theoretical foundation to investigate how the emotional valence of streamer speech and real-time comment influence live streaming performance (sales growth/fans growth) and explored the moderating effect of the live streaming atmosphere cues. With Python software and natural language processing technology of Baidu AI platform, sentiment analysis was conducted on 124,085 streamer speech sentences and 24,3767 viewer real-time comments. Our findings reveal that both positive and negative emotional valence of streamer speech positively affect live streaming performance; in addition to the negative impact of neutral emotional valence on sales growth and of negative emotional valence on fans growth, real-time comment emotional valence has a positive correlation with live streaming performance; finally, the study examined the moderating effect of atmosphere cues and demonstrated the complex dynamics of atmospheric cues affecting emotional contagion and sales in live streaming. The findings provide a scientific reference for live marketing managers to optimize the emotional expression of streamer speech and their live streaming operation mode.