Text Analysis for Depression Detection: Mental Health Digital Transformation
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IOS Press
Abstract
Depression is a pervasive mental health disorder affecting millions globally. The rise of social networks and their digital footprint provides a unique avenue to leverage AI for early identification of users who may be suffering. We built upon BERT for feature extraction from individual user posts, followed by a Convolutional Neural Network for classification. Since the pre-trained BERT model may not effectively capture social media language, we propose an approach to pre-train BERT on Reddit data before integrating it into the BERT+CNN architecture.Description
Keywords
AI, Depression, Digital Health, Digital Mental Health, NLP, AI, Depression, Digital Health, Digital Mental Health, NLP, 46 Information and Computing Sciences, 4608 Human-Centred Computing, Mental Illness, Prevention, Mental Health, Depression, Behavioral and Social Science, Brain Disorders, Machine Learning and Artificial Intelligence, Mental health, 3 Good Health and Well Being, 0807 Library and Information Studies, 1117 Public Health and Health Services, Medical Informatics, 4203 Health services and systems, 4601 Applied computing
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Studies in Health Technology and Informatics, ISSN: 0926-9630 (Print); 0926-9630 (Online), IOS Press, 329, 1948-1949. doi: 10.3233/SHTI251293
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© 2025 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).