Academic
Publications
Predicting box-office success of motion pictures with neural networks

Predicting box-office success of motion pictures with neural networks,10.1016/j.eswa.2005.07.018,Expert Systems With Applications,Ramesh Sharda,Dursun

Predicting box-office success of motion pictures with neural networks   (Citations: 24)
BibTex | RIS | RefWorks Download
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 network to models proposed in the recent literature as well as other statistical techniques using a 10-fold cross validation methodology shows that the neural networks do a much better job of predicting in this setting. q 2005 Elsevier Ltd. All rights reserved.
Journal: Expert Systems With Applications - ESWA , vol. 30, no. 2, pp. 243-254, 2006
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
    • ...Due to its ability to solve some problems with relative ease of use, robustness to noisily input data, execution speed and analysing complicated systems without accurate modelling in advance, ANN has successfully been implemented across an extraordinary range of problem domains that involves prediction and a wide ranging usage area in the classification problems [1-8]...

    Sébastien Salvaet al. Accelerating Learning Performance of Back Propagation Algorithm by Usi...

    • ...It has been applied to various data mining tasks [3-5]...

    Li Zhouet al. Study of influence factors of customer satisfaction based on BP neural...

    • ...Intelligent predictive models also have been developed to forecast the financial performance of a movie at the box-office before its theatrical release is explored [3-5]...
    • ...The accuracy rates of the SVM, RS and NN models in Test A2 using the inputs (FWAN [0, 1, 2], FWSN [0, 1, 2], and AR [0, 1, 2, 3]), and the output, TAN [0, 1, 2] are better than the models of the other tests in Test A. Table IV shows Test B models built by varying the hidden neurons, the range of an output attribute and the number of training and testing records...
    • ...Test A2 models having input value ranges, the first week audience number [0, 1, 2], first week screen number [0, 1, 2], and audience review [0, 1, 2, 3], and an output value range, total audience number [0, 1, 2], have shown better accuracy rates than the models of the other tests in Test A. The models in Test B13, which have the value range of 0 [less 700,000], 1 [700,000 – 3,000,000] and 2 [over 3,000,000] have shown better accuracy ...

    Chang-Joo Yun. Performance evaluation of intelligent prediction models on the popular...

    • ...Sharda and Delen [8] have treated the prediction problem as a classification problem and used neural networks to classify movies into categories ranging from ‘flop’ to ‘blockbuster’...

    Sitaram Asuret al. Predicting the Future with Social Media

    • ...Due to its excellent performance, ANN model has been applied to various data mining tasks such as exchange rate estimation, stock price estimation, market segmentation, churn prediction and box office success predictions [5, 6, 25]...

    Hyunchul Ahnet al. Using Hybrid Data Mining Techniques for Facilitating Cross-Selling of ...

Sort by: