Foursquare Hack Day Project Using Maponics Neighborhoods

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We wanted to point you to an interesting internal project from engineers at Foursquare using Maponics Neighborhood Boundary data.  Engineers matched 1,500,000,000 check-ins globally to the neighborhoods in which they took place.  Using the resulting data, they determined the top categories based on location check-ins in each neighborhood and created a profile that reflects how people work and play in that neighborhood.

Algorithmically, they were then able to compare neighborhoods across different cities. For example, they determined which three neighborhoods in San Francisco were most similar to New York City's East Village based on top check-in categories.

Want to know the three neighborhoods in San Francisco most similar to the East Village? Get the results and learn more at Foursquare’s Neighborhood Experiment.

Visit our Customer Use page for more interesting uses of neighborhood boundaries.