Text Analysis for Depression Detection: Mental Health Digital Transformation
Date
Authors
Madanian, Samaneh
Gao, Yuan
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
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
Source
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).