Sentiment Analysis of Online Products using Ratings and Reviews

Every second, we can observe a massive surge of data being generated. Data present abundantly needs to be processed to become meaningful information. One way of processing data and knowing the current trend is through product analysis. This concept can be used by organizations to identify their flaws and enhance their productivity. It is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs. In this project, we throw light on the aspect that data generated by textual comments along with the rating contribute the efficient classification of data rather than only the rating and obtain various insights as a part of the analysis. In general, when a person wants to buy a product, he checks for the review of the product and then makes a decision whether to buy or not. In more specific terms, the user checks only the rating and makes a decision. We have understood that sometimes rating is misleading the customers and it alone cannot be the sole parameter to take a decision hence we are comparing ratings and comments for better efficiency and authenticity of product reviews.