Precise Dissemination of E-Commerce Information and Behavior of Social Media Users

Abstract

In order to solve the problem that the e-commerce system provides users with more and more choice information, it makes it difficult for users to find the desired products in a large amount of product information, and a research method for accurate dissemination of e-commerce information and behavior of social media users has been proposed. In order to improve the individual sales method of merchants, a method of multiangle analysis of data is proposed by clustering algorithm and classification algorithm. Research shows that there is a big difference between men and women in the use of WeChat, with women accounting for 70%. It can be seen that the respondents were mainly women. People aged 26-40 account for 62.4%, which matches the main consumer group (26-40 years old) in the industry research report. In terms of monthly disposable income, the median and mode are both between 1,000 and 2,000 yuan, which is related to the age distribution of the respondents. The frequency of online shopping 1-6 times/month accounted for 81.5% of the overall sample, and the online shopping experience for more than 1 year accounted for 98.8%, indicating that the respondents generally have the habit of online shopping. Through experimental analysis, the effectiveness of the improved algorithm is verified. In terms of online shopping consumption accounted for the total consumption, the number of people accounted for one-fifth and one-third. It can be seen that online shopping is an indispensable part of people’s daily consumption.