Mental Health Status and Influencing Factors of College Counselors Based on Social Psychology

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Yong Ye

Abstract

In order to further improve the mental health of college counselors, a recommendation algorithm is proposed based on social psychology to study the mental health status and influencing factors of college counselors. Methods: This algorithm analyzes the influencing factors of the user's mental health by calculating the feature vector on the basis of user's preference and similarity for the social environment resource. The matrix vector of resource similarity is constructed by the calculated cosine similarity, and the context modeling hierarchical model is constructed. Results: The user's preference matrix for resources is calculated, so that a personalized recommendation algorithm based on label and collaborative filtering is proposed. Finally, the algorithm and model proposed are validated. Experiments show that when the value of N is 10 or 15, the recommendation algorithm by label can improve the recommendation accuracy and recall rate, which indicates that the proposed algorithm can significantly improve the quality of recommendation results. Conclusion: Therefore, the algorithm proposed can effectively improve the recommendation quality of college counselors' choice of colleges to alleviate psychological stress.

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