Sentiment Analysis on E-Learning Using Machine Learning Classifiers in Python

Abstract

In today’s virtual world, E-learning frameworks are becoming more and more popular. Online courses turn out to be very trendy as it provides a virtual online educational platform where anyone can take education at their place. Online education also provides all types of courses to all age groups. But it is also observed that students dropout and low completion rate in E-learning has emerged. This paper review some papers on the opinion of students on E-learning and Mooc Data is taken from twitter with the help of a scraper written in python. Around 500 tweets were taken from twitter. This paper is focused on finding the accuracy of sentiment polarity as positive or negative. After finding the polarity, accuracy percent has been calculated with the help of three classifiers that are Naïve Bayes, SVC, and Logistic Regression. Hence, this technique may help online education providers to enhance and exceed the growth of services.