Hindi and Kannada Twitter Sentiment Analysis Using Machine Learning Algorithm

Sentiment analysis is an important task in natural language processing. Twitter sentiment analysis (SA) is the most frequently researched discipline today. Only a few researchers have concentrated on multilingual twitter sentiment analysis, while the majority of scholars have worked on English twitter sentiment analysis. Recently, there seems to be a large increase in the quantity of data sets transmitted via social media in a variety of languages. This work examines the semantic nature of a text in order to classify positive and negative tweets using Hindi and Kannada language models, respectively. Machine learning models such as Naïve Bayes Classifier, KNeighbors’ Classifier, Decision Tree Classifier and Random Forest Classifier are used to tackle the classification task.