Predicting Movie Success (VAST Challenge 2013)

Problem: 

VAST Challenge 2013 Mini-Challenge 1 is about predictive visual analytics. You are asked to predict the success of movies to be released in Spring 2013. The success is measured both by revenue (box office "take", i.e. ticket sales) and by viewer ratings.

More details: http://boxofficevast.org

Aim: 

You will be asked to predict how well a set of movies will do at the box office in terms of box office "take" (ticket sales) and how well they will do in the eyes of the viewers (the movies’ viewer ratings) for their opening weekend in the U.S.

A key feature of the challenge, though, is that contestants will use visual analytics to support their movie analysis and show us how it was used in their analytic processes. So, while the two numeric predictions would be possible to provide by plugging lots of data into a model, we will ask some additional questions to go along with the predictions that will require a human-in-the-loop and hopefully some outstanding visualizations

Members of the IEG group will support you in developing your predictive analysis and in supporting it with appropriate visualization tools.

Other information: 

The VAST Challenge committee will highlight outstanding achievements with recognition and awards as posted on this site as the Challenge proceeds through the year. Awards will be certificates that will be handed out at the 2013 VIS Conference in Atlanta in October.

Contestants will also be allowed to submit 2 page papers about their submissions for inclusion in the conference proceedings. Contestants will also be allowed to exhibit a poster at the conference. Award winners may also be asked to present their work during the VAST Challenge workshop; details will be determined later in the year.

Previous knowledge: 
Good experience with visualization and analysis tools such as R, MATLAB, Tableau, SAS/JMP, etc.
Scope: 
SE
Scope: 
BA
Scope: 
PR
Scope: 
MA
Assigned as: 
Project/Projektarbeit
Contact: 

Bilal Alsallakh, by appointment, alsallakh [at] cvast.tuwien.ac.at

Student(s): 

Philipp Omenitsch

Area: 
Visual Analytics (VA)
Status: 
closed