indranil143/Mental-Health-Sentiment-Analysis-using-Deep-Learning

A deep learning project using fine-tuned RoBERTa to classify mental health sentiments from text, aiming to provide early insights and support. ⚕️❤️

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Emerging

This project helps identify mental health sentiments from text, like social media posts or online discussions. You provide text content, and it classifies it into categories such as Anxiety, Depression, Stress, or Suicidal, along with a probability score for each. This is designed for mental health professionals, social workers, or community managers monitoring online content to understand emotional cues and offer timely support.

No commits in the last 6 months.

Use this if you need to quickly assess the mental health sentiment expressed in written text to inform early interventions or public health insights.

Not ideal if you need to perform real-time, high-stakes clinical diagnosis, as this tool is for early detection and insight, not a substitute for professional evaluation.

mental-health-support social-media-monitoring public-health crisis-intervention community-management
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 16 / 25

How are scores calculated?

Stars

35

Forks

7

Language

Jupyter Notebook

License

MIT

Last pushed

Jul 15, 2025

Commits (30d)

0

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