Abstract:
Film is an art medium that consists of a composite collection of basic media such as literature, music, painting, photography, drama etc.It has surpassed the basic media.Film has a reputation as an influential medium and one of the best tools of education. Its popularity is steadily increasing among people and all over the world. A movie review introduces a movie to the audience. Film analysis can play a role in developing the audience's perception of the film.Movie review establishes an effective link between the audience and the director.Criticism establishes an effective link between the audience and the director.Similarly, movie review analysis is now an important topic all over the world. Movie analysis is important not only to understand movies but also to know people's interest or people's emotions.Sentiment analysis is the most commonly used method for predicting user evaluations .It is the art of analyzing data on what people, public truly thinks about your business, text, opinion, social media etc. It’s an incredibly powerful tool in analytics toolkit.To analyze reviews, we must count the number of positive and negative words in a given text .Machine learning algorithms can help to understand whether a movie review is positive or negative.In this research, we discussed how to predict positive and negative reviews of movies using machine learning approaches.
