Stanford researchers are using computer algorithms that can see and learn to analyze millions of publicly available images on Google Street View to determine the political leanings of a given neighborhood just by looking at the cars on the streets.
The algorithms were trained – or more accurately, they trained themselves – to recognize the make, model and year of every car produced since 1990 in each of more than 50 million Google Street View images from 200 American cities.
The data on car types and location were then compared against the most comprehensive demographic database in use today, the American Community Survey, and against presidential election voting data to estimate demographic factors such as race, education, income and voter preferences.
The research team found a simple linear relationship exists between cars, demographics and political persuasion.
For instance, if the number of sedans in a neighborhood is greater than the number of pickups, there is an 88 percent chance that the precinct will vote Democratic.
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