Journal ArticleDOI
Predicting box-office success of motion pictures with neural networks
Ramesh Sharda,Dursun Delen +1 more
TLDR
Comparison of the use of the neural network in predicting the financial performance of a movie at the box-office before its theatrical release 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.Abstract:
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.read more
Citations
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Proceedings ArticleDOI
Predicting the Future with Social Media
TL;DR: It is shown that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors and improve the forecasting power of social media.
Journal ArticleDOI
Review: Neural networks and statistical techniques: A review of applications
Mukta Paliwal,Usha A. Kumar +1 more
TL;DR: A comprehensive review of articles that involve a comparative study of feed forward neural networks and statistical techniques used for prediction and classification problems in various areas of applications is carried out.
Journal ArticleDOI
Whose and what chatter matters? The effect of tweets on movie sales
TL;DR: The study investigates whether and how Twitter WOM affects movie sales by estimating a dynamic panel data model using publicly available data and well-known machine learning algorithms and reveals the potential values of monitoring people's intentions and sentiments on Twitter and identifying influential users for companies wishing to harness the power of social broadcasting networks.
Journal ArticleDOI
Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data
Márton Mestyán,Taha Yasseri,Taha Yasseri,Taha Yasseri,János Kertész,János Kertész,János Kertész +6 more
TL;DR: It is shown that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.
Journal ArticleDOI
A comparative analysis of machine learning techniques for student retention management
TL;DR: Analytical models to predict and to explain the reasons behind freshmen student attrition are developed and revealed that the educational and financial variables are among the most important predictors of the phenomenon.
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