Start Date
16-8-2018 12:00 AM
Description
In this paper, we first identify and formulate several Hollywood golden rules to specify relationships between certain characteristics of movies (e.g., budget size, release date, listed actors, and reviews) and revenue. Then we train well-known classifiers such as decision tree and neural network models to validate some of such golden rules and graphically present our findings. Our findings partially support several golden rules related to genre, WOM and sequel. We find that the more ratings a movie has, drama genre, or if the movie belongs to a collection show similar characteristics to movies that are have great budget recovery.
Recommended Citation
Wood, Morgan and Kim, Yong Seog, "Validating Hollywood Golden Rules: A Preliminary Study" (2018). AMCIS 2018 Proceedings. 23.
https://aisel.aisnet.org/amcis2018/DataScience/Presentations/23
Validating Hollywood Golden Rules: A Preliminary Study
In this paper, we first identify and formulate several Hollywood golden rules to specify relationships between certain characteristics of movies (e.g., budget size, release date, listed actors, and reviews) and revenue. Then we train well-known classifiers such as decision tree and neural network models to validate some of such golden rules and graphically present our findings. Our findings partially support several golden rules related to genre, WOM and sequel. We find that the more ratings a movie has, drama genre, or if the movie belongs to a collection show similar characteristics to movies that are have great budget recovery.