Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Predicting Gross Box Office Revenue for Domestic Films

  • Song, Jongwoo (Department of Statistics, Ewha Womans University) ;
  • Han, Suji (Department of Statistics, Ewha Womans University)
  • Received : 2013.04.16
  • Accepted : 2013.07.08
  • Published : 2013.07.31
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Abstract

This paper predicts gross box office revenue for domestic films using the Korean film data from 2008-2011. We use three regression methods, Linear Regression, Random Forest and Gradient Boosting to predict the gross box office revenue. We only consider domestic films with a revenue size of at least KRW 500 million; relevant explanatory variables are chosen by data visualization and variable selection techniques. The key idea of analyzing this data is to construct the meaningful explanatory variables from the data sources available to the public. Some variables must be categorized to conduct more effective analysis and clustering methods are applied to achieve this task. We choose the best model based on performance in the test set and important explanatory variables are discussed.

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Cited by

  1. Pre-production forecasting of movie revenues with a dynamic artificial neural network vol.42, pp.6, 2015, https://doi.org/10.1016/j.eswa.2014.11.022