Software Predicts Movie Success

scheming daemons writes "TechNewsWorld has an article about software that predicts whether a movie will be successful or not by factoring in its rating by censors (e.g. G, PG, R), strength of the cast, genre, competition from other films at the time of release, special effects, whether it is a sequel, and the number of theaters in which it will show."

Comments

What about the most important part?

[Spazntwich]

A good script?

Re:What about the most important part?

[delirium_9]

You must be new here. You don't need a good script to make a succesful movie. Just ask George Lucas (or Arnie, Charlize, Julia, Brad,...)

Program??

[malraid]

I can do this with Excel and some previous statistics! How breaktrough it this? Of course, if it's a program that analyzes the script, that would be another matter, but it's not.

Music Industry Did This Too

[gasmonso]

The big recording labels had developed software to determine the quality of song. Apparently, they could determine if a song would be a megahit or a flop. Judging from what I've heard on the radio, it doesn't seem to work. Hopefully the movie industry will have better success.

http://religiousfreaks.com/

Re:Music Industry Did This Too

[owlstead]

No, hopefully, they won't have (better) success. More sucky movies can only be the result of this.

More data than they need

[Dr. Spork]

If this thing does any good predicting at all, I'm sure it's based on the number of screens that the movie shows on. Once you have that number, I'm sure your pick will usually be pretty close. This is because the theater companies pay public opinion eggheads big bucks to figure out how many screens to reserve for movies... based on the movie's expected audience draw. These theater people do the actual analysis. To piggyback on their results and then pretend you were the insightful one seems really ... unimpressive.

overtraining.

[goombah99]

Yet another example of some machine learning bozo overtraining on a dataset to come up with a perfect predictro of historical data with little value for generalization. No doubt they have some dull understanding of cross validation which they mistakenly believe assures they have not over trained. Heh. In the end just as good as your linear numTit predictor.

And then when they are done they find that any future predictve power it has only is focused into a couple of clusters that any fool could have told you were sure bets. It has not value unless your goal is to recycle the same things over and over till there's just one tru formula that all money making movies must follow.

I suspect movie making is probably a lot like the stockmarket. While there's general themes that always have positive returns, the can't be a formula for big success because if there were then once it was known it would not work anymore. Originality and a cyclic nature of traditional themes is the flow but not predictable.

garbage in, garbage out

[spirit_fingers]

This is what happens when the bean counters try to quantify the creative process. You can add up all the ingredients for a hit movie and still have a major bomb on your hands.

It's like saying you can dump fois gras, Chateau Latour, beluga caviar and a savoy truffle into a blender and end up with the world's most wonderful milkshake. In the end it's a recipe for mediocrity, at best. More often, all you get is expensive puke.

If one could predict success by adding up the elements that go into movie making, then "Catwoman" should have been the megahit of 2004.