Metatags for Geographic Locations. GeoURL ICBM Address Server is a location-to-URL reverse directory. This will allow you to find URLs by their proximity to a given location. Find your neighbor’s blog, perhaps, or the web page of the restaurants near you.
Add yourself to the database.
For an example, check for sites near New York City and San Francisco. You can also get an RSS feed: see New York City RSS and San Francisco RSS (the RSS has an attached XSL stylesheet, so if your browser supports it, you will actually be able to see a reasonable rendering.)
Why is it called an “ICBM Address?” Old Usenet historical precedent [Smart Mobs]
Took me about 30 seconds to add myself to the database.
Blog Tribe Social Network Mapping.
Here is the initial social network analysis of the Blog Tribe at Ryze — which maps the Friendship networks and Blogrolls of Tribe members. What’s unique about this collaborative project is the mapping of blogspace and of how two unique communities intersect.
Thanks to the contributions of Valdis Krebs, Pete Kaminski, and those who volunteered to contribute their blogrolls, this is one of the largest online communities mapped. The data was captured within a month of the founding of the Blog Tribe, a snapshot in time that will be useful to return to, with 1,108 nodes from approximately 100 members. [full story]
[Ross Mayfield’s Weblog]
This seems like an appropriate item to launch 2003 with. I was one of the contributors of data for this experiment, so if you dig into the pictures and such you’ll find my name in there.
Ross did a great job pushing this along. He’s also tracking some of the early reactions to the data from others. Phil Wolff makes an interesting observation on the underlying differences between the Ryze and blogging environments. Most of the social network analysis efforts I’ve seen tend to look at reasonably homogeneous environments such as organizations. We did something along those lines in the early days at Diamond, when we worked with Wayne Baker from the University of Michigan to look at the network structure within our partner group. Very helpful to see the underlying structure of even a relatively small network of executives within a single organizations.
As I reflect on this particular analysis, I’m struck by the potential to find additional insight in mapping the bridges between multiple networks. Here we have a group who all belong to two explicit networks. How can we use these tools to get a better sense of how to more effectively navigate through half a dozen different yet interconnected networks?