Mapping a City’s Flow Using #UberData

 

In this #UberData post we show how the 9 major US cities “flow” — and how people move from one part to another.

  • Boston
  • Chicago
  • DC
  • LA
  • New York
  • Philadelphia
  • San Diego
  • San Francisco
  • Seattle

Here is San Francisco’s network visualizing the probability that a ride starts in one neighborhood and ends in another:

San Francisco

The neighborhoods are outlined in grey and at the centroid of each neighborhood is a circle, the size of which represents the proportion of rides that flow out of that neighborhood. The circles are colored according to which statistically-identified subnetwork they belong. Every neighborhood that sends a ride in has a line of the same color as the source neighborhood connecting it to its destination. The weight of each line represents the proportion of rides that go from the source neighborhood to its target. (Technically speaking this is a weighted digraph.)

In this case, as with before, most of the action is going on between neighborhoods in a radius around downtown San Francisco. What about the other cities?

Boston

Chicago

Washington, DC

LA

New York

Philadelphia

San Diego

Seattle

What can we do with this information? Well we can identify networks of “related” neighborhoods that are the “hub” of the city, into and out of which the most people flow.

Here are the most tightly connected neighborhood pairs for each city:

  • Boston: Back Bay-Beacon Hill / Boston Central
  • Chicago: Near North Side with itself (…guess people don’t want to leave!)
  • DC: Capitol Hill / Downtown
  • LA: WeHo with itself
  • New York: Midtown with itself
  • Philadelphia: City Center West / City Center East
  • San Diego: Mission Bay with itself
  • San Francisco: SoMa with itself
  • Seattle: Capitol Hill with itself

What’s amazing is that, in most cities, people tend to stay within a neighborhood taking relatively short rides.

What is it about Near North Side, WeHo, Midtown, Mission Bay, SoMa, and Capitol Hill that make them so popular? These neighborhoods have some kind of activity gravity keeping people within them, and that’s fascinating.

What variables account for this? Is it because people tend to live, work, and play in the same neighborhood? Do they have the most popular bars, restaurants, and cultural centers?

Cities are amazing places and #UberData can give us a peek into their style like this.

Sign Up to Ride
Featured articles

Less Traffic, More Jam

A typical ride: you request, have small talk with your driver, and safely get where you need to go. For Jonathan, a driver-partner in California, his rides are anything but ordinary — he wants his passengers to have fun and turned each trip into a dance party — and now the latest viral video. We caught up with the man in front of the cam to learn more about what inspired him to create this feel-good video.

Making Our Roads Safer—For Everyone

A new report conducted in partnership with Mothers Against Drunk Driving (MADD) reveals that when empowered with more transportation options like Uber, people are making better choices that save lives.

In the Driver’s Seat: A Closer Look at the Uber Partner Experience

New technologies are creating opportunities no one could have imagined. To understand Uber’s place in that trend, we commissioned a survey of our driver-partners and put together a comprehensive analysis.