Abstract
In this research, the objective is to collect a large amount of live streaming data over a long period of time, to argue the micro problems of live streaming e-commerce environment (live streaming book selling e-commerce) with big data, how to efficiently interact with viewers to convert live streaming traffic into subscribers, to discuss the moderating effect of the number of live interactions between live streaming traffic (viewership) and the number of new subscribers, and to discuss the influence of demographic characteristics (gender, age, geographic regions) of viewers as control variables. This research applied Python data crawling, and took into account 1,664 live streaming events from the top ten book publisher accounts in China from January 1 to June 30, 2022, and 52,788,900 live comments, and conducted a statistical analysis of the data to discuss the research hypotheses. The research results that anchors should cater to the reviewers and interact with them according to their psychological needs in a timely manner. In addition, anchors should appropriately guide interactions at live streaming events, control the pace of the live streaming events, allocate a reasonable amount of time to demonstrate the products, answer to questions raised by viewers and guide them to subscribe their live streaming accounts. The value is an attempt to explain the cause-and-effect in social science with big data, thus to offer experience for live streaming e-commerce companies to improve their marketing performance.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
