Abstract
SentimentSense is a Django-based web application that performs sentiment analysis on user-provided text. Using Natural Language Processing (NLP) and machine learning models, the system classifies text into positive, negative, or neutral sentiments. It provides an interactive interface for real-time sentiment prediction and visualization.
Existing System
Traditional sentiment analysis methods rely on manual review or basic rule-based and keyword-based techniques. These approaches often lack contextual understanding, accuracy, and scalability for handling large volumes of data.
Proposed System
The proposed system, SentimentSense, is developed using Django to provide a user-friendly web interface integrated with advanced NLP models. It enables real-time sentiment prediction, improved contextual understanding, scalable processing, and structured result visualization for better decision-making.
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english
