Sentiment analysis on product reviews

Abstract

Sentiment analysis is used for Natural language Processing, text analysis, text preprocessing, Stemming etc. are the major research field in current time. Sentiment analysis using different techniques and tools for analyze the unstructured data in a manner that objective results can be generated from them. Basically, these techniques allow a computer to understand what is being said by humans. Sentiment analysis uses different techniques to determine the sentiment of a text or sentence. The Internet is a large repository of natural language. People share their thoughts and experiences which are subjective in nature. Many a time, getting suitable information about a product can became tedious for customers. Companies may not be fully aware of customer requirements. Product reviews can be analyzed to understand the sentiment of the people towards a particular topic. However, these are voluminous; therefore a summary of positive and negative reviews needs to be generated. In this paper, the main focus is on the review of algorithms and techniques used for extract feature wise summary of the product and analyzed them to form an authentic review. Future work will include more product reviews websites and will focus on higher level natural language processing tasks. Using best and new techniques or tool for more accurate result in which the system except only those keywords which are in dataset rest of the words are eliminated by the system.