Opinion Mining of Customer Reviews for Online Products through Sentiment Analysis

Abstract

Sentiment essentially relates to feelings; attitudes, emotions and opinions. Sentiment Analysis refers to the practice of applying different Data Mining techniques to identify and extract subjective information from a piece of text. A person’s opinion or feelings are for the most part subjective and not facts, which means to accurately analyze an individual’s opinion or mood from a piece of text can be extremely difficult. Sentiment Analysis has gained much attention in recent years due to the importance of the automation in mining, extracting and processing information in order to analyze an individual’s opinion or mood from a piece of text. These days, Internet has become a valuable place for exchanging ideas, learning skills, sharing reviews of a product, service or movies, it makes hard to understand or identify the user’s emotion from the list of available online reviews. With Sentiment Analysis from a text analytics point of view, I am essentially looking to get an understanding of the attitude of a writer with respect to a review in a piece of text and its polarity; whether it’s positive, negative or neutral. There are different techniques and algorithms that can be used for sentiment analysis on opinion mining. This paper performs the extraction of opinions and emotions of customer from product reviews using data mining and natural language processing techniques. It focuses on opinion mining from product reviews and discusses the characteristics of reviews and describes different methods to extract corresponding opinions.