An active CL community is a requirement for anywhere I live, and this awesome “chalkboard map” by John Nelson of IDV Solutions shows a re-imagining of the USA, broken down by the cities with a craigslist community and the zipcode area that is serviced by those.
The USA of CL IDV page has notes about using this data as an overlay for online mapping services. It also gives a fascinating breakdown of the process involved in compiling the data and creating the map information:
• Scrape the list of Craig’s cities at http://www.craigslist.org/about/sites.
• Split joint-locations into individual locations (like “Odessa / Midland”)
• Geocode place-specific locations.
• Manually position the more regional locations (like “Southeast Iowa”).
• Divide locations into three geographically distinct regions (split by the Continental Divide along the spine of the Rockies and the Mississippi); duplicate any locations that meaningfully straddle a border, like St. Louis. I do this to introduce some true-cost of crossing either of those features, in the face of an algorithm that would otherwise treat the whole country as a smooth unfettered plain.
• Run Voronoi (Thiessen) algorithm to generate best-fit zones for the points, for all three regions.
• Clip Voronoi zones by a “land” shape to cut out the oceans and provide a common border between the three regions (my “land” was constructed from the Census Bureau’s tracts file).
• Merge the 3 regional Voronoi sets into a unified nation-wide set.
• Dissolve boundaries between same-website Voronoi zones (to re-combine the joint-locations up there in step 2) into merged chunky polygons.
• Manually re-assign oddly-orphaned or split areas (common along complicated shorelines).
For any of you data-hounds, or those who just like infographics, check out all the cool maps and visualizations these guys are creating.
Update: Mr. Nelson left a nice comment with some details about an additional Craigslist map he created a few months after this one, that plots the actual zip code details instead of polygon shapes based on the general areas they represent. Check it out below, and if you want the actual zip code data table (like one Linkedin user did), navigate to the page for the dropbox link and notes.