Semantic classification of Twitter data

Social media has become an important information source with the expanding internet and ideas shared by the people. The social media raw data which is quite disordered and messy can not be processed as it is and obtain adequate results. In this study, sentiment analysis has been performed by collecting data from the Twitter. To perform this analysis an intelligent system has been created by using machine learning methods such as Naïve Bayes, Random Forest, Support Vector Machine and the compared results has been given.