KSK@DravidianLangTech 2025: Political Multiclass Sentiment Analysis of Tamil X (Twitter) Comments Using Incremental Learning
Kalaivani K S, Rashmi Sanjay, S. M. Thissyakkanna, S. K. Nirenjhanram · 2025
The introduction of Jio in India has significantly increased the number of social media users, particularly on platforms like X (Twitter), Facebook, Instagram.While this growth is positive, it has also led to a rise in native language speakers, making social media analysis more complex.We took part in the shared task to classify political comments to classify social media comments from X (Twitter) into seven different categories.Tamil speaking users often communicate using a mix of Tamil and English, creating unique challenges for analysis and tracking.This surge in diverse language usage on social media highlights the need for robust sentiment analysis tools to ensure the platform remains accessible and user-friendly for everyone with different political opinions.In this study we trained four machine learning models, SGD Classifier, Random Forest Classifier, Decision Tree, and Multinomial Naive Bayes classifier to identify and classify the comments.Among these, the SGD Classifier achieved the best performance, with a training accuracy of 83.67% and a validation accuracy of 80.43%.