Approaches for Sentiment Analysis on IMDB Movie Reviews

Movies have evolved into large business where people are spending billions of dollars, and with increasing in demand, the prices of tickets are increasing rapidly. Due to increasing rate of tickets’ prices, people cannot afford to go and watch the movies every month. So, most people first read the review of a particular movie and then decide whether to watch it or not. Sentiment analysis is the way to classify user views from the different piece of content. There are lots of social networking platforms where we can use sentiment analysis to get an overview of public thoughts or opinions on any topic. Nowadays with increase in the use of Internet, a lot of people are connected to Internet, and they are using social media and e-commerce sites and often post their opinions and reviews. So, sentiment analysis helps us to categorize whether the comment is positive or negative. This paper examines sentiment analysis on IMDB movie reviews’ data. We have proposed a new approach of natural language processing and sentiment classification in Internet movie Database (IMDB) dataset and have calculated the accuracy of various ML algorithms to find out the positive and negative comments on a movie.