Comparison of Classification Algorithms on Twitter Data Using Sentiment Analysis

2020 International Journal of Advanced Trends in Computer Science and Engineering  
For the past few decades tremendous effort were dedicated for sentiment analysis. One of the uses of sentiment analysis is to get customers view of a product or company. In this paper we have explored sentiment analysis using two classification algorithms i.e. Support Vector Machine (SVM) and Naïve Bayes considering the positive and negative sentiments using the twitter dataset. Our implementation results indicate that SVM provides the best accuracy which is followed by the Naïve Bayes.
doi:10.30534/ijatcse/2020/179952020 fatcat:awzqyifkxzbh5efbvkvrcey4ry