Abstract
Hollywood and the business of making movies has been in existence for over 100 years and has faced several changes both in business and technology. With data becoming more integrated into everyday life, businesses have now started to use data to change the way that they make decisions. However, the movie making industry does not appear to be taking advantage of this trend. It was after the release of the movie Jaws that Hollywood had its new business model which is being followed to the present day. Interest in the combination of the existing Hollywood business model and the emerging technology of data and business analytics, is the driver for the research, in which we examine what factors are most beneficial to a movie's success and if this success can be predicted. The research focused on measuring the success of a film by looking at how much money a movie made in total worldwide sales and how much money a movie actually made when taking into consideration the cost of producing the movie. With sales as our measure, the research then took the other variables of a movie's release, rating, length, genre, how much it cost to make, what audiences thought about the movie, and who was in charge of making the movie (distributor, director, writer, and star) to see if certain actors, directors, and stories are better predictors than others. The research accomplished this through creating linear and logistic regression tests, decision trees, and random forest models. The research found that the monetary success of a movie can be predicted with a 1 percent mis-labeling error. However, there was still a considerable amount of over-prediction as opposed to underprediction.
Advisor
Huang, Qimin
Department
Statistical and Data Sciences
Recommended Citation
Galbraith, Alexandra, "Lights, Camera, Profits: Exploring What Makes a Movie Profitable and if this can be Predicted Through Statistical Approaches" (2024). Senior Independent Study Theses. Paper 10910.
https://openworks.wooster.edu/independentstudy/10910
Disciplines
Analysis | Applied Statistics | Business Analytics | Categorical Data Analysis | Data Science | Numerical Analysis and Computation | Other Film and Media Studies | Statistical Methodology | Statistical Models
Keywords
Data Analysis, Data Prediction, Movies, Movie Profits, Movie Success
Publication Date
2024
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2024 Alexandra Galbraith