With millions of viewers globally, live streaming is a new social media that can deliver video content in real time and with many social interaction functions. Our research aims to understand the personality traits and the motivations of active live streaming viewers as well as their user behaviors in the general population in China. Our results indicate that extraversion was negatively associated with live streaming use, while openness was positively associated. The main motivations to watch live streaming were social interaction, information gathering, and entertainment, and they were associated with different frequencies of use and genre selection. Financial tipping behavior was positively associated with social interaction. Furthermore, motivations mediated the effects of personality traits on live streaming use. People high in openness were more likely to be motivated to chat by information needs. Among extraverts, those who were more social watched fewer streams. We demonstrated that personality traits and motivations can jointly predict live streaming use. The current study not only provides the first evidence of live streaming use with personality traits and motivations but also expands the perspective on individual difference with the mediation analysis. Practically, the person-situation joint interpretation can give industry a clear indication on how to design personalized user experience for people with different personality traits and motivations.

Based on the theory of planned behavior (TPB), the current study developed a model to understand motivations and predictors of viewers’ virtual gifting behaviors in online live streaming. The model was tested with data from 392 live streaming viewers with previous virtual gifting experiences. The results showed that perceived pleasure, interaction with streamers, group interactions, and support for streamers can predict individual attitudes toward virtual gifting. Subjective norms learned from family and friends as well as streamers and viewers in live streaming could significantly affect virtual gifting intention. Quality of streams, the attractiveness of the streamers, and viewers’ monetary resources influenced perceived ease of virtual gifting. Overall, the proposed model predicted virtual gifting behavior well. Findings were discussed in terms of the links between online and offline subjective norms along with the relationship of perceived behavior control, virtual gifting intention, and virtual gifting behavior. We suggest that the adjusted TPB model with subjective norms both offline and online can fit the online interaction contexts well and explain online norms development. Furthermore, our model reflects how social incentive contributes to virtual gifting. These findings offer insights into the motivations of virtual gifting behavior and provide implications for virtual gifting experience design.