Sentimental Analysis using Naive Bayes Classifier

Sentimental Analysis is mainly meant for classifying the text based on its polarity. Opinion Mining is one of the major categories in sentimental analysis. Opinion of any user in buying a product or rating a movie contributes highly to the product or movie For example: If a movie is given various levels of star rating, then the other audience who think of going for the movie might have a overview on the rating and then decide whether to prefer the movie or not, similarly the reviews of any kind of product might change the thought of any buyer in buying the product. In this project Naive Bayes classifier technique is being used for the purpose of classification. The dataset used here is the amazon product review dataset obtained from the UCI repository. The dataset consists of about 600 records and every record is being analyzed using the Naïve Bayes approach, this is a probabilistic approach and finally the result is obtained in a form of matrix. The accuracy of the proposed approach is finally calculated with the help of the confusion matrix.