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2006

Predicting box-office success of motion pictures with neural networks

11 years 9 months ago
Predicting box-office success of motion pictures with neural networks
Predicting box-office receipts of a particular motion picture has intrigued many scholars and industry leaders as a difficult and challenging problem. In this study, the use of neural networks in predicting the financial performance of a movie at the box-office before its theatrical release is explored. In our model, the forecasting problem is converted into a classification problem-rather than forecasting the point estimate of box-office receipts, a movie based on its box-office receipts in one of nine categories is classified, ranging from a `flop' to a `blockbuster.' Because our model is designed to predict the expected revenue range of a movie before its theatrical release, it can be used as a powerful decision aid by studios, distributors, and exhibitors. Our prediction results is presented using two performance measures: average percent success rate of classifying a movie's success exactly, or within one class of its actual performance. Comparison of our neural ne...
Ramesh Sharda, Dursun Delen
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where ESWA
Authors Ramesh Sharda, Dursun Delen
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