Sentiment Analysis of Keenly Intellective Smart Phone Product Review Utilizing SVM Classification Technique

There is a massive increase in number of people who access various social networking and micro-blogging websites that gives new shapes the impression of today's generation. Many reviews for a specific product, brand, individual, and movies etc. are helpful in directing the perception of people thus the analysts are begun to create algorithms to automate the classification of distinctive reviews on the basis of their polarities in particular: Positive, Negative and Neutral. This automated classification mechanism is referred as Sentiment Analysis. The basic idea behind this paper is to apply support vector machine (SVM) classification technique to classify the sentiments of smart phone product review which analyses datasets used for classification of sentiments and texts. Data sets are also used for learning and testing purpose and implemented by SVM methods for finding the polarity of the ambiguous tweets. The obtain results show to achieve high accuracy as predicted on the basis of reviews of smart phone.