Sentiment Analysis for Text Feedback Approaches

Abstract

Sentiment analysis can be account for web content mining of different feedbacks from social platforms, online products, organizations, events, employees. Collecting feedbacks is considered facile but extracting insights out of it is still challenging. Dramatic increase of internet utilization around the world raised up the amount of  feedback data which is a challenge to manage and classify the sentiments. It is been motivated for companies to get more meaningful and actionable insight from their feedback data that will help them to improve their products also it will be convenient for the customers to choose the right product in lesser time. In this system we will see all the different approaches used for sentiment analysis which includes lexicon-based, machine-learning and hybrid approaches. Opinions of people in feedback analyzed for english words and sort the texts in positive and negative reviews for which there must be one or more positive or negative word. To create pool of words firstly it  selects  words having sentiments and from reviews of product using standard approaches it mines the polarity and hence opinion mining is carried out for the betterment.