IDENTIFYING E-LEARNER’S OPINION USING AUTOMATED SENTIMENT ANALYSIS IN E-LEARNING

Abstract

E-learning is becoming more powerful and popular medium for learning through online. It is very important to identify the opinions of the users of E-learning. E-learning commonly refers to teaching efforts propagated through the use of computers to impart knowledge in a non traditional classroom environment. It is difficult to find the users mind whether they are satisfied with the E-courses. Sentiment analysis helps to find about the users who are visiting the E-learning portals. Sentiment analysis refers to the use of natural language processing text analysis and computational linguistics to identify and extract subjective information in source materials. It aims to determine the attitude of speaker or a writer with respect to some topic or overall contextual polarity of a document. Automated sentiment analysis helps to identify the sentiment of the users from the E-portal pages in which users generally browse on a topic or area they are interested. This information can be used by E-learning system to identify the user's emotional factors and can analyse the user's activity each time. The user's sentiments towards a course can serve feedback for E-learning portals in online learning environment. In the proposed E-learning system the automated sentiment analysis helps to analyse the E-portal visited pages by the user. This helps the developer and educator to know where the learner concentrating on specified areas with any manual work or any feed backs from the user. Here for automated sentiment analysis the Bayesian statistics classification, Naive Bayes classifier is used.