Application of Lightweight Freshmen Group Portrait Based on Echarts

Abstract

This study designs a general analysis model for fusion method, big data portrait of young users using map engine data, and tries to solve the problem of fusion of qualitative and quantitative methods in user portrait. This paper determines the necessity of freshmen group portrait in the practice of ideological education by studying the freshmen group portrait and its objectives, connotations and roles; through the various aspects of data collection, cleaning, structuring, data analysis and modeling, the Echarts platform is used to establish a data visualization example, to achieve a three-dimensional, multi-dimensional and interactive visualization output of the freshmen group portrait, and with the help of the combination of qualitative and quantitative methods, the design of the Research model. Based on the theory of sociological psychology, we construct a user value map, use Look-alike algorithm to construct the map data labeling system, use K-Means clustering algorithm to get the data results, and analyze the data results for business. Using the model for big data empirical demonstration, the results show that young users can be divided into 20 categories of groups, and the total number of data results reaches 170 million, and the number of preference labels reaches 606, which is better than the results of survey data. And it is applied in the initial education and teaching practice process, obtaining better results, with replicable and generalizable practical application scenarios.