Construction and Prediction of Students' Multiattribute Social Network Based on Psychological Big Data Analysis

Abstract

In view of the limitations of the current research on students' single attribute psychological problems. In this paper, a multiattribute social network model was constructed based on students' social data and psychological label data, and the improved MANE algorithm was used to solve the problem to predict students' psychological problems. In addition, DeepWalk and Node2vec network embedding algorithms were used to embed students' multiattribute social network, respectively, so to verify the effectiveness of the model. Finally, based on the prediction model of students' psychological problems, this paper uses Django web framework, MySQL database, and Bootstrap framework to design a personality prediction system, including data storage, algorithm training and prediction, result display, and other modules.