How to Predict a Movie's Success at the Box Office
Sharda and Delen describe the widely publicized and very successful model they have created to predict the financial performance of a movie before its release to the theaters. Based on neural networks, the model attempts to classify a movie into one of nine categories, ranging from a "flop' to a "blockbuster." Key factors used in the classification include MPAA rating, expected release month, star value, genre, level of special/technical effects, number of screens the movie is expected to open on, and whether or not it is a sequel. Examples of blockbuster movies that the model predicted correctly include Spiderman, Star Wars: Episode II, Harry Potter and the Sorcerer's Stone, Lord of the Rings: The Fellowship of the Ring, and Shrek. The model missed by under predicting the blockbuster success of My Big Fat Greek Wedding and by predicting success for Waterworld, which fell short. Copyright International Institute of Forecasters, 2006
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