This research is in an effort to increase the profits of movie theaters in China. It is with no doubt that
the movies which a theater decide to show differ in the revenue that they contribute. With that in mind,
this research aims to identify movies that are more likely to generate higher revenue because:
1. If the demand for a particular movie is too low in comparison to the supplied amount of
shows and venues, the movie theater will incur a loss.
2. If the demand for a particular movie is very high in comparison to the supplied amount of
shows and venues, the movie theater will not be able to maximize their revenues.
We retrieved data about information of the movies both in China and Taiwan ( i.e Movie Title, type,
directors, actors, released date ) , the responses towards the movies from Taiwanese customers ( i.e # of total comments, # of actual rating, # of expected rating, actual rate, expected rate) , and the box office revenue of both countries.
We used the information about movies in Taiwan to predict the box office revenue of movies which
will be released in China. Data visualization allowed us to get a quick vision of the effects and
correlation among the predictors and the outcome variable. Various data mining strategies and models were then applied from which the most successful model was chosen. Only the visualizations that deemed meaningful to us were added to the appendix.
According to the box office revenue we predicted, movie theaters in China can better arrange their
shows and venues. Furthermore, they will also know which factors have significant influence on their