An effective machine learning approach for sentiment analysis of restaurant reviews

Abstract

Sentiment analysis or opinion analysis is creating a vast area of research in this modern era of social media. Various blogs and Social Medias (Facebook, twitter, Instagram) are the most popular platform for the users or consumers where they frequently express their opinion about current topics, various brands, restaurants, movies, books, traveling places etc. Sentiment analysis is a very smart and effective approach to find peoples view about a particular news/ place/restaurant/movie/book/brand. It is beneficial for the both service providers or sellers and consumers. Researchers in the areas of natural language processing, data mining, machine learning, and others have tested a variety of methods of automating the sentiment analysis process. In this research work, I used restaurant reviews dataset to analysis the sentiment and for this approach Gaussian Naïve Bayes method is proposed based on coupling classification methods using arcing classifier and their performances are analyzed in terms of accuracy.