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@article{181524,
        author = {Afiya Mohammad and Dipti Bangde and Aditi Charlawar and Hrutuja Tiple and Tanzila Sheikh and Dr. Manisha More},
        title = {sentiment analysis on online product reviews},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {4396-4399},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=181524},
        abstract = {Imagine having a direct line to your customers' thoughts, understanding exactly how they feel about your products. That's precisely what our project delivers: a powerful, user-friendly web platform that digs into online product reviews using smart machine learning. We built this to help businesses truly grasp customer opinions, spot what's working well and what needs a tweak, and make decisions based on real data, not guesswork. Whether you're an e-commerce giant improving product quality, a product manager fine-tuning features, a marketing pro sensing brand vibe, or a customer service hero tackling urgent issues, this platform is your secret weapon. Our system is built on a robust architecture, featuring a sleek React frontend, effortless file uploads, cutting-edge ML processing, an intuitive results dashboard, and even an AI Chatbot for deeper insights. Just upload your review data (CSV/JSON), and watch as it's transformed through preprocessing, analyzed by multiple machine learning algorithms simultaneously, and then visualized through interactive charts. The integrated AI Chatbot takes it a step further, offering conversational analysis and helping you uncover hidden gems in your data.},
        keywords = {Customer Insights, AI-Powered Feedback, Product Intelligence, Machine Learning for Reviews, Interactive Dashboards, Natural Language Processing, Business Growth},
        month = {June},
        }