AI Case Study

Fox predicts likelihood of watching movies at theatres based on trailers with machine learning

20th Century Fox has collaborated with Google Cloud to predict how likely people are to see movies in theaters based on their trailers. Merlin, the machine learning system, is capable of recognising patterns in movies to understand their scenes. After describing a scene with objects like "car" it can use other movies and attendance records to make predictions on what people who have watched this movie are likely to watch next.

Industry

Consumer Goods And Services

Entertainment And Sports

Project Overview

"Data scientists at 20th Century Fox and Google Cloud have developed machine-learning software that can analyze movie trailers and predict how likely people are to see those movies in theaters.

A recent preprint research paper breaks down how the program, named Merlin, can now recognize objects and patterns in a trailer to understand movie scenes. Merlin can scan trailers and spot objects like "man with beard," "gun," "car," and decide whether the movie is an action flick or a crime drama based on the context in which those objects appear.

Merlin can use its knowledge of common tropes in trailers to understand how sequences of actions in trailers play into our expectations for genre films. For example, Merlin knows that cars going fast may break into a car chase "followed by a car flipping, and a car explosion." A car chase with explosions is very likely in an action movie, so Merlin can use that information to tag the movie with "action" and "car chase," and in turn use that to recommend other movies with car chases.

Merlin compares these tags to a large dataset that includes hundreds of movies and millions of attendance records. Fox and Google claim that the data is "fully anonymized" and "user privacy-complaint," but it’s not clear exactly what data is included or how it is gathered. According to the paper describing Merlin, the system pairs attendance records with “basic demographics information” at the individual level.

Beginning with 2017's The Greatest Showman, 20th Century Fox has been using Merlin's predictions to decide which movies to make and how best to market them, according to a Google blog post.

Here's the thing, though: art doesn't work like that. There are many factors that can make a movie successful that can't be identified by a computer, even one that can correctly identify a beard. Movies have silent performances, jokes, and harder-to-quantify intangibles that even real humans struggle to explain. This is why good movie criticism is compelling: there are infinite ways to analyze what movies do, how, and whether that is "good" or "bad"."

Reported Results

"To see Merlin’s limitations, we can look a its analysis of Logan, the 2017 superhero western from director James Mangold, which Google used as a test-case in its blog post. Merlin watched the trailer for Logan and tagged every object it recognized, like "vehicle," "car," "man," "facial_hair," and, most frequently, "tree."

According to Merlin, if you saw Logan, you'll most likely pay to see The Magnificent Seven, Jason Bourne, John Wick 2, and The Legend of Tarzan. It's easy to see how "man," "beard," and "gun" would draw recommendations for The Magnificent Seven and John Wick 2, but I suspect Tarzan was chosen mostly on the strength of "tree." Out of the top five movies that real audiences saw prior to Logan, Merlin only got one ( John Wick 2) correct. Jason Bourne and Tarzan weren’t even in the top 20."

Technology

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Strategy

Strategic Planning

Background

Benefits

Data

movies, movie trailers, and millions of attendance records