Google Says It Can Predict Which Films Will Be Huge Box-Office Hits | Hacker News Reader

Google Says It Can Predict Which Films Will Be Huge Box-Office Hits

businessinsider.com

32 pointsgivan18 comments

This is essentially just Google using their search data to replace the tracking polls that movie studios do already. It's not hard to predict a movie's box office right before it comes out, but what good does that do you, since all the money has been spent already?

Exactly, this would be a awesome predictions if it started earlier in the production, like at the kernel of the idea or even at the first draft of a script before it's even green lit. Studios have been trying to predict what will be hits since the early part of the 20th century and they still get it wrong. This just seems to draw a correlation to marketing of a movie or buzz to dollars spent at box office, which is the magic behind the studio industry.

It's not hard to predict a movie's box office right before it comes out

Well, there's the Netflix prize[0] which tells otherwise

Predicting movie appreciation is actually very hard to solve. One of the infamous examples is the "Napoleon dynamite problem"[1]

[0] http://en.wikipedia.org/wiki/Netflix_Prize

[1] http://www.techdirt.com/articles/20081123/1212542927.shtml

The Netflix prize results show that recommending movies that an individual viewer is likely to enjoy is, in certain cases, a hard problem. That doesn't say much about the difficulty of predicting a movie's aggregate popularity over a large population.

IIRC the netflix prize is about making predictions for individual users based on their history & interests, which is orders of magnitude harder than making a prediction for the average over all users, which is all that you need for box office predictions.

They are measuring buzz/some sort of interest. If buzz is not there, you could pump more money into marketing and see if it raises the buzz. That's probably the only thing you can do that late into the game, marketing spending.

Based on this, why aren't movie studios creating trailers based on minimal treatments, releasing them with dates a year or two in the future and then only creating the movie if the data shows that it'd be a blockbuster? Basically Lean development for movies.

Granted, I think we'd miss out on potentially great movies, but it seems like a way for the studios to further reduce their risk, so I think they'd be all over this. Perhaps they're already doing it and I'm just unaware.

Well it's Google's search data... this isn't public information.

Shhhh... don't tell anyone, I'm only sharing this with you:

http://www.google.com/trends/

I would guess part of what is being measured is enthusiasm to go see the movie in the near future. I tend to only search on upcoming movies that I am thinking about going to see.

There are also early adopters on movies. I follow some projects even before they start shooting.

> Based on this, why aren't movie studios creating trailers based on minimal treatments, releasing them with dates a year or two in the future and then only creating the movie if the data shows that it'd be a blockbuster? Basically Lean development for movies.

Because this might work for a little while, but then very quickly people would learn that most trailers were for movies that would never come out and start tuning them out.

Plus, getting cast, directors, etc., to sign on to a project when the only thing guaranteed is small payment for a trailer based on a minimal treatment would be difficult, and part of what the trailer promotes and audiences respond to is the cast, director, etc.

Lean in the movie business would look very different than lean in software (just as lean in software, while borrowing lots of ideas from lean in traditional manufacturing, looks different) because the context is different.

I am not sure "predict" is the correct word here.

It's still a prediction, even if the immediate interpretation is that they have some ability to predict before they start filming/not in the few months before release.

IBM has made a similar claim using Twitter's Firehose and natural language processing to determine a general overview of people's feelings towards a film. The solution was to tell the film advertisers to toss out more engaging trailers. It all seemed somewhat odd. Pay IBM tons of bucks just to be told you should probably make more trailers (which would most likely fail too.)

They have so much data they can "predict" a lot more about you.

Check for Granger Casuality?

This is a resubmission of this: https://news.ycombinator.com/item?id=5838570

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