The Use of Supervised Text Classification Techniques: A Comprehensive Study

Every second in social networking, a massive amount of feedback, comments, and posts are made, resulting in a massive increase in the social database. It's now necessary to go through enormous amounts of data to figure out how people feel about a certain company or product. Most online evaluations are published in English, but as technology and people's understanding improve, Hindi-language material is becoming more prevalent on the internet. In addition, knowing people's views about a particular item is an important component of Indian language sentiment analysis; we consider all of their thoughts to be equally valid. To boost the accuracy of our categorization, we used the Hindi language repository for general news stories from a number of news sources. Text classification accuracy was investigated using Naive Bayes and other machine learning classification techniques, as well as Random Forest, Support Vector Machines, and Logistic Regression approaches.