Movie Review in Python

Information visualization with the movie's trend of audiences and reviews becomes important. Movie makers are not only want to know their movie's popularity based on the number of audiences but also check their movie's evaluation from people who see the movies. If they hope that the movie is a box office hit, they should identify the correlations between audiences and reviews. Our visualization tools try to find the movie's moods by using normalized graphs and showing the relationships. Experiments on real dataset from a movie site (naver-movie.com) and Korean Film Council containing the number of customers in each movie. We find some unique relations and discover the word-of-mouth effects from our results.