Sentiment Analysis of Polarity in Product Reviews In Social Media

Abstract

Sentiment analysis is the study area in Natural language processing (NLP) that is concerned to identify the mood or opinion with in the text. This paper emphasizes on the different methods utilized for classifying the natural language text reviews in accordance with opinions expressed in text to analyze whether the extensive behavior is negative, positive or neutral. The abundance of discussion platforms, Weblogs, product reviews sites, e-commerce and social networking sites have encouraged stream of thoughts and articulation of opinions. Social media is considered to be a big platform of sentiments, reviews and opinion evaluation. Data used in this study are online product reviews collected from twitter and used to rank the best classifier for sentiments. The method of analysis on polarity classification was discussed in experimental work by using well known classifiers including Naïve byes, Support vector machine and Logistic regression for predicting the user reviews.