Date of Award

6-2023

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2023.

Department

Computer Science and Engineering

First Advisor

Yi Fang

Abstract

Filmmaking is a financially high-risk field of work. There are multiple variables that contribute to a movie’s success or failure, however the most impactful ones have yet to be identified. In this paper, we used publicly available datasets in combination with several forms of analysis models to determine common factors associated with historically successful movies. Our results narrowed the top categories to include the runtime, the production budget, the release year, the genres, and the primary language. The final round of analysis yielded an 84% accuracy, after the usage of XGBoosting and gradient boosting. Further improvements to this project could involve testing different modeling techniques to improve accuracy, as well as using an expanded dataset that includes more films from outside of the United States.

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