Enhanced Framework for Sentiment Analysis in Text using Distance based Classification Scheme

Social media platform like blogs, social networks and content communities have become valuable resource for mining the sentiments. In fact information gained from the social platform like Facebook and twitter has been expressed to be more important to industries, market, news, public opinion organization and many more. Sentiment analysis in a text is a procedure in which the polarities like positive and negative of a specified text is determined. In this project we are using twitter comments as the text input. The proposed method consists of two phases called testing and training phase. For extracting the features we are using the sentiwordnet. The distance based classifier is used to classify the features. Finally analyses of the sentiments are done by polarities classified by the distance classifier.