A Study towards the Sentiment Analysis Techniques for the Analysis of Customer Review Data

Abstract

          Sentiment Analysis (SA) is an automated method of classifying views as positive, negative and neutral. Analysis of sentiments in text sources like emails, reviews on products on online shopping websites, posts on social media platforms like Facebook, Twitter offers businesses with significant acumens to understand the reason behind customers' choices and behaviour. It incorporates computational study of actions of an individual in connection with his purchasing interest and then mining his sentiments about an organization’s commercial entity. This entity can be envisioned as product experience, an event, and post on the blog or individual. Besides recognising the opinion, the systems employing opinion mining/sentiment analysis also mine characteristics of the expression like: polarity: positive, negative or neutral opinion, subject: the object being discussed, opinion holder: the individual stating the opinion. This paper focuses on comprehensive outline of sentiment analysis techniques grounded on recent research and consequently discovers various rule based, machine learning and deep learning approaches in context of Sentiment analysis over customer review data set.