Sentiment analysis with XAI algorithm for movies recommendation

Movie streaming platforms rely on recommendation systems to suggest films, but users often don’t understand how these recommendations are made. This study combines Explainable Artificial Intelligence (XAI) and sentiment analysis to create a recommendation system that not only suggests movies but also explains why they are recommended. By analyzing user moods and matching them with movie features, the system uses content-based filtering to provide personalized suggestions. XAI techniques make these suggestions clear and easy to understand, building trust and improving the user experience. This work shows how explainable systems can make movie recommendations smarter and more user-friendly.