Hybrid deep learning framework classifies mental distress in social media users, indicating potential for timely intervention.
This paper proposes a hybrid deep learning framework using BERT and BiLSTM for early detection of mental distress from social media content. The system integrates contextual embeddings, temporal sequence learning, and sentiment-behavioral analysis to classify users into different mental health risk levels.
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Fawaz Maqhdoom Shariff (2026) studied this question.
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