Application of Big Data Technology in the Research on Mental Health Education of College Students from Poverty-Stricken Families

Abstract

In the information age, the big data technology has been applied to all walks of life, bringing a new angle of thinking to personal life and social development. The mental health education problems have been increasingly prominent among college students and gradually become a focus of attention from universities and colleges, families and society due to the particularity of their identity and severity of their impacts. Affected by various factors, these students are more susceptible to some unhealthy mental states and mental problems in daily study and life. In this paper, the K-means clustering algorithm and C4.5 decision tree algorithm were used to establish mental health databases based on the Hadoop technology. The limitations of physical space were broken through and those of static data were improved through the data collection and processing, storage and management, analysis and mining, etc., so as to realize the accurate recognition, comprehensive mastery, coordinated development and active forewarning of students from poverty-stricken families. This study can further enhance the timeliness and pertinence of mental health education among college students from poverty-stricken families and drive the students to welcome healthy growth and become useful persons.