When it comes to a neighborhood’s political leanings, look no farther than the cars or pickups on the street.

Researchers at Stanford University used a computer algorithm to sift through 50 million Google Street View images from 200 cities across the U.S. – and what they found was that vehicles are a shockingly good predictor of whether a neighborhood votes Republican or Democratic.

In neighborhoods with more sedans than extended-cab pickup trucks, there’s an 88 percent chance voters picked a Democrat at the polls, researchers said. And the opposite was true as well, the study found: In neighborhoods where pickups outnumber sedans, there’s an 82 percent chance an individual precinct went Republican.

The election data researchers looked at was from the 2008 presidential race between Barack Obama and John McCain, researchers said. The research was published Tuesdays in the Proceedings of the National Academy of Sciences.

“Using easily obtainable visual data, we can learn so much about our communities,” said Fei-Fei Li, director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab, where the research was done.

Li added that what can be gleaned from cheap or publicly available data is often “on par with some information that takes billions of dollars to obtain via census surveys.”

While Li’s team may not have paid millions for their data, it did take a lot of work to train computers to comb through millions and millions of images.


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