LegisAI: AI-Powered Legislative Comment Analysis
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Abstract
The increasing volume of stakeholder feedback in legislative processes makes manual analysis inefficient and error-prone. This paper presents LegisAl, an Al-based system designed to automatically analyze legislative comments using Natural Language Processing techniques. The system performs sentiment analysis to classify opinions, generates concise summaries of lengthy comments, and visualizes frequently used keywords through word clouds. Transformer-based models such as DistilBERT and DistilBART are utilized to achieve efficient and accurate processing. The proposed solution significantly reduces manual effort and enhances decision-making by providing structured insights. Experimental results demonstrate an approximate accuracy of 85% in sentiment classification with effective summarization performance.
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