Movie Ratings and Reviews Sentiment Analysis using Python

This project involved analyzing movie ratings and user reviews from a Kaggle dataset to uncover trends and viewer sentiments. I used Python libraries such as Pandas for data manipulation, Matplotlib and Seaborn for data visualization, and NLTK for natural language processing. The analysis included identifying top-rated genres, average ratings per year, and performing sentiment analysis on user reviews to classify them as positive, negative, or neutral. I visualized the sentiment distribution and correlated it with movie ratings to uncover patterns in viewer perception. This project showcases my ability to clean and analyze textual and numerical data, perform sentiment analysis, and communicate insights through compelling visualizations.