Sentiment Classification of Movie Reviews with Logistic Regression

This research focuses on developing an automated sentiment analysis system for Tamil text. The system utilizes Natural Language Processing (NLP) techniques, specifically the Bag of Words (BoW) model with CountVectorizer, to extract features from the text data. These extracted features are then fed into a Logistic Regression classifier to predict sentiment as positive, negative, or neutral. The system demonstrates an F1-score of 0.82, indicating high accuracy in sentiment classification. This research has significant implications for businesses and organizations, enabling them to effectively analyze customer feedback, monitor brand reputation, and make data-driven decisions based on public opinion.