Identification of Psychological Disorders of People Using Text Data and Bert Base Deep Learning Technique

Swapna Shyamrao Kulkarni and Prashant Prakashrao Agnihotri

International Journal of Scientific Research in Science and Technology, 2026, vol. 13, issue 4, 26-34

Abstract: The issue of psychological disorders remains a significant public health concern worldwide today, as there exist numerous people who have been identified to suffer from a variety of psychological disorders, including depression, anxiety, PTSD, and bipolar disorder. Early detection and diagnosis of the illness of body play a crucial role in the proper treatment of such patients; however, traditional medical techniques suffer from issues related to accessibility, stigma, and scaling. This paper proposes a methodology of automated identification and classification of psychological disorders through the analysis of the text based on a BERT model. Specifically, our method involves using a BERT pre-trained language model for identification and classification of the psychological disorder based on the labelled data consisting of social media texts and clinical data samples. Our model has been trained using five epochs with an optimal batch size. It has been found through experimental results that the use of transfer learning with a BERT model significantly surpasses classical machine learning approaches.

Keywords: BERT; psychological disorder detection; mental health; NLP; transfer learning; text classification; transformers; deep learning (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v13:y2026:i4:id:1720

DOI: 10.32628/IJSRST261342

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