Live streaming is an emerging industry derived from the Internet platform in the 21st century, which attracts many commercial resources with its complex categories and strong traffic monetization capabilities. Although a large number of high-quality talents have poured into the ranks of live streaming, live streaming can still divide the blue ocean track from the Red Sea market. At present, most of the existing live streaming research focuses on the normative governance of the platform department, the purchase psychology mechanism of consumers and the macro e-commerce live broadcast market development trend research, and there is still a lack of subdivision research on the live broadcast revenue of the live streaming category, the author obtains data through the live broadcast data analysis platform, using a multi-linear regression model for empirical research, and explores the live streaming category and other non-core variables such as the number of fans, the number of viewers per game, the unit price of customers, etc The degree of relevance to the revenue of the live broadcast. The study found that in the case of the same non-core variables, the average revenue (traffic realization ability) of live streaming goods was sorted from high to low as :( jewelry literary play> beauty personal care> home> daily necessities> men's and women's> food and drink> books>shoes and hats bags> maternal and infant products> Mobile digitally). By constructing the theoretical model of live streaming categories and live broadcast revenues, and taking the correlation between various variables and live broadcast revenue as the starting point, this paper expands the theoretical research of social self-media with goods categories, which helps practitioners to understand the development status of each category of live streaming from the model construction mechanism and conclusion data, so as to grasp the market trend and fully expand the blue ocean category. Create a live streaming market with a variety of flowers.
China's rural informatization construction has a good foundation. However, China's rural informatization construction still has a long way to go. It is not only facing major development trends such as integration, specialization, networking, multimedia, practicality, popularization, integration and whole process, but also facing the urgency of farmers' increasing agricultural income and farmers' demand for information services to open up a larger consumer market. Moreover, increasing grain production and farmers' income are not only the focus of the "three rural" issues, but also related to China's steady economic development and social stability. In the selection of variables, this paper uses the GDP of the primary industry to quantify the income of farmers, and uses the number of broadband households to quantify the degree of rural information networking. In terms of the development trend of rural information construction, this paper will study the rural information networking, test it by using Vif multicollinearity expansion factor method, and study the relationship between farmers' income and the degree of rural information networking by ridge regression method.
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