Uber (“the app-based on-demand private driver service”) is heavily into using its data. They actually have a group they call their “math department.”
Here is a post on AtlanticCities by one of their data scientists (who is also a neuroscience post-doc at UCSF). Lots of interesting time series data, shown for NYC & SF in particular (and apparently some PCA) culminates in the network diagram shown above.
In fact, we can quantify how city-like or not city-like any given neighborhood is. That is, we can ask, “how San Francisco-like is the Mission, really?” and “how much more like New York is the Financial District than it is San Francisco?”
And we can do this for every neighborhood. What do we find?
Cities have “stereotypical” neighborhoods that very strongly match the flow of their home cities, and some neighborhoods just don’t really seem to belong to their home city. They’re outliers.
Read more. [Image: Uber]