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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?
It seems their has been a recent spurt of "smart" systems like this...
Maybe we're finally coming out of the "AI Winter" it seems like we've been in for a decade or so...
td
hard core geek-ware
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/Napoleon Dynamite? I find it hard to believe that this script would have predicted the success of this film.
Also, this actually kind of disgusts me since it seems IMHO that it relies on the same formulaic approach that's responsible for the poor offerings that Hollywood is currently producing.
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.
Many of the criteria used here are subjective, and based upon existing human estimation of the movie's success. For instance, when a movie opens in a large numbers of theatre's simultaneously, it usually means people have already predicted it will be successful. Also, movies are often chosen to 'Open' on a date that doesn't conflict with other movies, and is chosed to maximise revenue. It's a real stretch to call this software's process 'scientific'.
"...strength of the cast..."
Will it be based on looks or on acting ability? There would be some serious issues if they used acting abilities. There are some horid actors/actresses that sell boatloads because they look great, and then there are some...well...less visually pleasing folks, that are fantastic actors/actresses.
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.
This sort of "equation" has it's basis in Quackery, and has been around for years; if I cared enough I think IIRC, that we even had the "equation of a Sitcom" posted and discussed here earlier on.
Howzabout we actually get an article that's worth discussing? This submission is pathetic.
Go ahead mods, do yer worst. I refuse to swallow this tripe.
A couple fans told me that my last journal entry was mint; give it a shot. Hope you like.
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.
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." It's ridiculous to expect software to predict entertainment. From the above, success can only be even remotely predicted by "the number of theaters in which it will show". And possibly the "strength of the cast". Mainly I think the trailers shoved down our throat with only the best parts of the movie could help success. I highly doubt this software would have predicted the success of The Blair Witch Project. Zero special effects, zero strength of the cast, zero budget.
Hollywood uses similar metrics for most of their features.
This explains more than anything else why the quality of the majority of movies dropped so fast in the last few years.
None of those parameters can measure (digitally) the quality of the story, quality of acting (note: not popularity of the cast, Pam Anderson is also popular) and quality of the movie anyway.
Hearing from buddies or critic reviews, that a movie is poorly done mix up of popular actors, effects and soft porn with dumb as stics scenario stolen from a bunch of action flicks from the past, is the fastest way to give up an average moviegoer from seeing it.
- Creating a formula based on your theories and finding that the data you run data through it is well explained by your (weighted) equation.
- Taking a bunch of numbers and having the computer find the best equation that explains the data.
One of those two methods is bad mathIf it took this Information Systems Professor 7 years of work to create his model, I seriosuly doubt that he picked Method #2 and I also doubt that you could have done this in an hour with Excel.Oh, and since this article has shitty information, if you check out google news, you'll discover they're using a nerual network to crunch their numbers.
[Fuck Beta]
o0t!
1. make a db of meta info for already released movies
2. make a software that conforms to the already existing stats and "guesses" the income. If it doesn't guess it, tweak until it "guesses" it.
3. pitch it to Holywood execs by demonstrating it "works" by entering the same movie info you have already tweaked it for
4. profit
Of course the fact that it has (well, relatively poor IMO - 37% success? 75% "sort of success"?) success with the db of 800 movies is a result of it been tuned to work for those stats, and there's totally no guarantee it'll work for future releases.
Especially that it can't and won't factor in the most important factor: does the movie suck after all or not.
This isn't perfect because how would Passion of the Christ or Mystic River fit into this algorythm. There were no special effects, both were rated R, and one was in a language that hasn't been spoken for 2000 years. This is the problem with Hollywood today, they think there is a formula to good movies, good movies are good because they have a good plot, not high payed actors or special effects out the waazoo.
King Kong is flopping like a pancake...
Please tell me you're not basing that statment on a total of three days of release time! Try making a more correct statement in two months or so.
Guy asked me for a quarter for a cup of coffee. So I bit him.
Most of the factors it uses depend on a human already deciding that a movie's going to be a success. You don't get a star studded cast unless you think it's going to be a hit. You don't spend lavishly on special effects unless you think it's going to be a hit. And distribution size is determined by its commercial potential. When that's already decided, there's not much point to having a computer algorithm say the same thing.
What would be particularly interesting is to examine the movies it failed on and attempt to understand why.