Online Product Grading using Sentimental Analysis with SVM

This paper implements a system that provides a user an authenticated score of any online product computed with the help of the NLP technique called Sentiment Analysis and Opinion Mining. Sentimental Analysis is the anatomization of the judgment of a user on a particular product. It scans through the sentences in search of keywords that deliver definite emotions. In our system, we have used a Support Vector Machine (SVM) classifier to generate a fine-grained Sentimental Analysis report. This classifier helps us to categorize the reviews collected from the product’s website URL into predefined categories to affirm the user’s thought process and generate a rating from 1 to 5 (1 being the lowest, 5 being the highest). The system makes use of this technique to gather all the accrued reviews and convert the textual meaning into a meaningful average grade. This process makes it possible for any prospective customer to have a definitive conclusion on the review of the product.