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A Machine Learning-Enhanced Chat Application for the Identification of Mental Disorders
- 1 School of Computer Science, Wuhan University, Wuhan 430072, China
- 2 Bishop Guertin High School, Nashua, NH 03060
- 3 Magee Secondary School, Vancouver, BC, Canada, V6M 4M2
- 4 Westridge School for Girls, Pasadena, CA 91105
* Author to whom correspondence should be addressed.
Abstract
The prevalence of mental disorders is increasing, but they continue to be underdiagnosed and under addressed. Social media platforms offer novel opportunities for detecting potential mental health issues through the analysis of user-generated content. This paper presents a chat-based program developed using machine learning models trained on a dataset of comments from Reddit users. The program is capable of predicting the type of mental illness based on user input. This study provides a detailed comparison of various classification algorithms, including Naïve Bayes, Logistic Regression (LR), Support Vector Machines (SVM), and Random Forests (RF). Additionally, the paper discusses relevant machine learning techniques from previous studies. The results indicate that LR model, particularly with a uni-gram feature representation, outperforms other models with an accuracy of 0.81 and demonstrates the fastest processing speed. Future research directions include the integration of Large Language Models and the development of a multilingual chat interface.
Keywords
Social media, mental disorder, machine learning, classification algorithm
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Cite this article
Cao,Q.;Yan,Z.;Gong,Z.;Huang,J. (2025). A Machine Learning-Enhanced Chat Application for the Identification of Mental Disorders. Applied and Computational Engineering,132,11-19.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation
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