Analysis and Research of Students’ Mental Health Status Based on K-Means Clustering Under the Background of Big Data

Abstract

With the continuous improvement of the quality of education in our country, mental health is one of the important basic conditions for students to become talents, and the management of students’ mental health has received more and more attention from the society. Traditional student mental health management generally still stays at the establishment of questionnaires, and the application of data only stays at the stages of addition, deletion, modification and investigation. With the development of big data and artificial intelligence, We should elevate data analysis and application to an objective, visual, and predictable level, and take precautions and early warnings for student mental health management. This article uses data analysis technology to develop a student mental health data analysis platform based on the R-Shiny framework. The platform model uses the K-Means clustering algorithm to make full use of student data, scientifically and efficiently analyze the mental health of students, which is helpful for early warning and targeted scientific mental health counseling and management for students.