Alex Larson
539 Fall 2013
Predicating Movie Box Office Performance
Project Proposal
The movie industry is a large part of modern day culture. With the rise of websites like Netflix,
where people are able to watch hundreds of movies at any time, it is evident that film is a large part of
our culture today. Movie studios are always trying to come up with the next big thing to make the
largest profit. Studios have been adapting books, plays, and comic books to cash in on an already
existing popular intellectual property. Studios have also been remaking older films in the hopes that
they will have the same level of success as its predecessor. Making a movie is an expensive endeavor
and people want to know if a remake, an adaptation, or an entirely new idea will be successful. Some
current examples of how things are being predicated as being done by data from sites like google and
Wikipedia. Studies have been done using the number of searches a movie gets on google or how many
hits a Wikipedia page gets for a certain movie to predict its box office success.
The above methods have been shown to work well but I also believe you can predict the success
of a movie based on many of its features. Some of these features may include genre, budget, release
date, which studio making the movie, if the movie is or is not a new intellectual property, actors
involved, MPAA rating (PG, PG-13, etc.), and many more. Using these features one should be able a
prediction of a movie’s potential box office success. I propose to use some artificial neural network
methods to classify and predict a movie’s potential box office success. Using some of the above features
of movies described above I would like to create a data set based on movies within the past few years.
After a good set of features and classes have been established, I will use artificial neural network
algorithms and experiment with various pattern recognition classifiers like Multi-Layer Perceptron
(MLP), k-nearest neighbor classifier, etc. to predict the potential box office success of a movie.
References:
Mestyán M, Yasseri T, Kertész J (2013) Early Prediction of Movie Box Office Success Based on Wikipedia
Activity Big Data. PLoS ONE 8(8): e71226.doi:10.1371/journal.pone.0071226
Chen, Andrea, Panaligan Reggie (2013) Quantifying Movie Magic with Google Search
http://boxofficemojo.com
http://www.the-numbers.com