The Neighborhood Project is creating a map of city
neighborhoods based on the collective opinions of internet
users. Addresses and neighborhood data are translated into
latitude and longitude values, and then drawn on the map.
The address and neighborhood data are collected from
from people filling out the form below. The coordinates are
generated using the free geocoder.us
. The map is
from the TIGER/Line
US Census data. Our first city is San Francisco, but we
will add more soon. Or you can download
the software and make your
This is an experiment in collective knowledge. The more
people who add their opinion to the database, the more
accurate the neighborhood boundaries become. Plese add your
The map is updated every night. We plan to make the data
we've collected available, once we get a little bit better
at working with PostgreSQL.
The algorithm for drawing neighborhoods is the "blobby"
algorithm, well known in computer graphics. You can think
of each point in a neighborhood as a little magnet, and the
neighborhood is the region where the combined attraction of
all those magnets is above a certain strength. A single
point makes a small circle on the map. The influence of a
number of nearby points will combine to make a curved blob.
Read more about blobbies:
To prevent duplicate postings or submissions from combining
to form larger and larger circles, the program discards
duplicate entries when it draws the map.
There are two problems with the way the map is being drawn
Multiple entries that are very close together combine to
form large blobs. We are experimenting with an
algorithm which reduces the individual contribution of
points as the number of points in that immediate region
There are a small number of posts that are very far
outside the neighborhood that they claim to be in.
(Currently there appears to be an Inner Sunset and a
Marina post in SOMA, and a SOMA post in Potrero Hill, a
USF/Panhandle post in the Sunset, and so on.) We may
develop an algorithm that discards data points that are
very divergent from the average or standard deviation
for that neighborhood.
Thanks to Jeremy Avnet, Jonathan Moore, Amber Clisura, theory.org and mosuki.com for inspiration and
The software to create these maps is available on GitHub.
It is licensed under the GNU GPL. It
is written in Python and
uses the PostgreSQL
database. It's also hella beta so be afraid, be very afraid.