Research On The Effect Of Streamers’ Characteristics On The Viewing Volume In Knowledge-sharing Live Streaming

In recent years,with the development of media technology,live streaming is becoming popular as a new way of communication and sharing.As a kind of live streaming,knowledge-sharing live streaming realizes the interactive communication between the streamer and the audience,and can effectively help streamer answer user’s questions compared with other forms of knowledge sharing.The existing research on knowledge-sharing live streaming mainly focuses on phenomenon description,audience motivation and behavior research and streaming platform optimization.The research on the characteristics of the streamer is very limited.However,streamers are key in linking audience and platform,so the research value of them can’t be ignored.In order to fill this research gap,this paper constructs a conceptual framework based on Elaboration Likelihood Model,classifies the characteristic factors of the streamer according to the peripheral route and the center route.And we put forward two moderating variables(live streaming style and price)based on utilitarian-hedonic theory and customer perceived value.After collecting large-scale data sets from Zhihu Live and using LSTM model to generate variables for live streaming style,the regression results showed that the center route had a positive impact on viewing volume,while the peripheral route variables had a negative impact,which means the audience is increasingly inclined to make a choice after detailed judgment.Among them,we find that the argument quality of information is particularly important and is the core variable that affects the viewing volume.At the same time,while hedonistic live streaming style is one of the means to attract viewers,too distinct hedonistic style reduces the positive impact of the central path variables on viewing volume.Finally,from the perspective of the applicability and classification of knowledge,we have also done expanded research and compared the differences between different categories.This paper clearly reveals the influence of the characteristics of the streamer in the knowledge-sharing live streaming,enriches the research in this field,and expands the application scope of Elaboration Likelihood Model.This paper also gives suggestions for improvement from the angle of streamers and platforms,and provides a constructive solution for the development of the live streaming.