Crunching all this data also means the Livehoods team can determine the most related livehoods—that is, the areas that are most visited by the same people.
“It’s a really interesting way to see a snapshot of the structure of the city,” says Livehoods team member and Carnegie Mellon graduate student Justin Cranshaw.
Sometimes there are surprises, too. I live in Livehood #44 in San Francisco, which covers much more ground than what I usually think of as my neighborhood, near the famous intersection of Haight and Ashbury. And the neighborhoods most related to mine aren’t exactly what I figured, either.
Beyond just being a resource for the curious, Livehoods can give residents better insight and understanding about their city, the researchers say. Sadeh suggests the data could be used to help stores determine where their customers are really coming from so they know where to advertise, or to make predictions about how changes—the addition of a Whole Foods supermarket, for example—may impact a neighborhood.
Already, urban planners in Pittsburgh have indicated an interest in working with Livehoods, Sadeh says.
“They are clearly seeing lots of different possible applications for this analysis,” he says.