Evaluation method of college students' psychological quality of innovation and entrepreneurship based on big data analysis

Abstract

In the process of innovation and entrepreneurship, college students have different degrees of psychological problems due to the influence of market environment and their level of professional knowledge. In order to accurately evaluate the psychological quality of college students' innovation and entrepreneurship, an evaluation method of college students' psychological quality of innovation and entrepreneurship based on big data analysis is proposed. The historical information data and real-time data flow of college students’ psychological quality of innovation and entrepreneurship in the data source are collected, and the association rule feature extraction method in big data analysis technology is used to fuse the collected data, and complete the preprocessing, then the preprocessed data are stored in the database. According to the construction criteria of the indicator system, the sick indicator cycle analysis method in big data analysis technology is used to build the evaluation indicator system of college students' psychological quality of innovation and entrepreneurship, and the evaluation model of college students' psychological quality of innovation and entrepreneurship is built by combining the self-organization feature mapping neural network. The experimental results show that the information contribution rate of the evaluation indicator system of this method is higher than 95%, and the accuracy rate of the evaluation result is higher than 98%, which can effectively and accurately evaluate the psychological quality of college students' innovation and entrepreneurship.