Research on Sentimental Analysis on Veganism

This project introduces a sentiment analysis system developed to gauge public opinions on veganism as a social justice movement. By employing machine learning algorithms—Support Vector Classification (SVC), Logistic Regression, and K-Nearest Neighbors (KNN)—the system categorizes text data into positive, negative, or neutral sentiments. A dataset of 50,000 text entries from Kaggle was preprocessed and converted using Term Frequency-Inverse Document Frequency (TF-IDF). Comparative analysis using accuracy, precision, recall, and F1-score determined the most effective model. The scalable system supports social media monitoring and public perception research, providing insights into societal views on veganism.