Prediction of IMDB Movie Score & Movie Success By Using The Facebook

Abstract

Movie industry is considered a high risk cultural industry. Prediction of the movie success before the release of a movie is of critical importance. Prior studies have been conducted to predict the movie success on the basis of sentiment analysis of movie reviews, IMDB score, tweets etc. However, this study implies the exploration of relationship b/w the Facebook features on the movie success and IMDB score. Two data sets were used for this study. Sentiment analysis of Facebook movie page was done through lexalytics to calculate the hype factor of that movie. A predictive model is developed that exploits Facebook features to predict movie success and IMDB score. Linear regression (LM) revealed that Facebook features are not solely important in the prediction of IMDB score and SVM shows the 84% accuracy in the prediction of movie success in terms of Hit and Flop; hence conclusion drawn is that the sentiment score of Facebook page will improve the accuracy of a prediction model for movie success.