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DropZero – Sentiment Analysis for MoCA E-Consultation

It addresses the challenge of analyzing large volumes of stakeholder and public feedback received through the Ministry of Corporate Affairs (MoCA) E-Consultation module. The solution automates sentiment classification (Positive, Negative, Neutral), generates summaries and word clouds, and provides real-time insights to support data-driven policymaking.

Objectives:

Automate sentiment prediction for public comments. Reduce manual effort and improve efficiency in reviewing legislative feedback. Generate actionable insights with summaries & word clouds. Support transparent and data-driven governance. Ensure scalability and responsiveness using asynchronous task handling.

Scope:

Applies to MoCA E-Consultation feedback on draft legislations. Workflow: CSV Upload → Sentiment Analysis → Word Cloud → Summary Generation. Decoupled architecture using frontend, backend API, and cloud-hosted database. Future scalability for AI dashboards, trend detection, and identity protection.

Tech Stack:

Frontend: HTML, CSS, Flask Backend: FastAPI, PHP Database: MySQL (cloud-hosted) AI/ML: Hugging Face Transformers (DistilBERT, RoBERTa) Programming: Python, PHP

Features:

Sentiment Classification (Positive, Negative, Neutral) Word Clouds for SUPPORT, CRITICIZE, and NEUTRAL categories Summaries for individual reviews & overall insights Bulk Data Upload & Processing (CSV support) Real-time Analysis & Visualization

Future Scope:

Scalable AI-powered dashboards Anonymity & Identity Protection for commenters Voice-enabled submissions Fake/Spam comment detection Trend detection for evolving public sentiment

References

Conclusion

DropZero demonstrates how AI can revolutionize public policy feedback mechanisms. By reducing manual review time, enabling instant insights, and ensuring scalability, this solution aligns with the vision of New India through innovation, efficiency, and transparency.

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