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."
A good script?
Trolling is a art,
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.
please excuse my apathy
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/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.
Hmmm...I wonder what it had to say about Waterworld...
New Snot Eunichs.
Suddenly I'm thinking of the measure of the greatness of poetry scene from Dead Poets Society. Right on. Yeah, I know, it's not about greatness, it's about box office success. I bet they left Gigli out of their tests.
must... stay... awake...
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.
Network President: Greetings, gentlemen. You already know my execubots: Executive Alpha, programmed to like things it has seen before.
Executive Alpha: Hey hey hey.
Network President: Executive Beta, programmed to roll dice to determine the fall schedule.
Executive Beta: (rolls dice) More reality shows!
Network President: And Executive Gamma, programmed to underestimate Middle America.
Executive Gamma: It's funny, but is it going to get them off their tractors?
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.
Some drink at the fountain of knowledge. Others just gargle.
I have my doubts this will work. Like, statistically speaking, John Ratzenberger, the guy that played Cliff on Cheers is very bankable actor, he'd been in Empire Strikes Back and a couple Superman films, and all six Pixar films, so his films have grossed billions of dollars. I guess a computer might pick him to play the villian in the next Batman film, but in real life there isn't a magic formula.
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.
With 9 revenue categories, correctly predicting the category 37% of the time (RTFA), is, ehem, unimpressive - a dartboard would guess correctly 11% of the time.
So we have a predictor that makes 0.63/0.88 ~= 70% as many mistakes as a dartboard. If you give it one category of "wiggle", it makes 0.25/0.66 ~= 40% as many mistakes as a dartboard.
People are making a lot of hay out of this. It tells you that small movies (opening on fewer screens) are very seldom blockbusters, and that heavily promoted movies almost always make at least ten million or so. How is this unexpected? I bet I could get similar predictive power using a SINGLE variable - the promotion budget for each of the films. If it could tell us something actually interesting (or useful to hollywood types) - like "why are some big budget movies successful while others are not?" - that might be worth something.
Also, the journalist is a nitwit - "North American ticket sales currently total $7.6 million."
The good and new comes from no quarter where it is looked for, and is always something different from what is expected.
This is unbelievable! Awesome-o has thought up 1193 different film ideas. 906 of which star Adam Sandler!
I am scientifically inaccurate.