Social networks by example

A bit of context for the previous post:

Let’s use Dave Winer’s scripting.com as an example. By looking at the social network of scripting.com, we see that Dave has a slew of people who read him, and also that he reads a number of other weblogs. These are Dave’s “social ties,” or the individuals that make up his personal social network.

This personal network exists within the context of the whole network of webloggers: for each one of Dave’s ties, that individual has a set of ties, and so on and so forth. By looking at the context of Dave within the whole network, we see that he is one of the most central figures, falling in at #10:

1. kottke.org, 1.00
2. evhead.com, 0.78
3. zeldman.com, 0.73
4. littleyellowdifferent.com, 0.73
5. harrumph.com, 0.71
6. jish.nu, 0.70
7. camworld.com, 0.56
8. plasticbag.org, 0.52
9. rebeccablood.net, 0.50
10. scripting.com, 0.46
11. blusihorange.com, 0.46
12. obscurestore.com, 0.46
13. megnut.com, 0.45
14. robotwisdom.com, 0.45
15. textism.com, 0.42

This is a list of the most accessable individuals in the weblog world, most of them just a few clicks away from any weblog (the score is normalized with respect to Jason). It just so happens that Dave’s success at finding topical news is related to his location in the network, as is the case across the board for webloggers.

I hope that this makes things a bit more clear. I’ve been researching in my head so much in the past week, my brain is in auto-pilot. Time to take back control of the wheel and start making sense. More statistics later! It’s quite exciting to see what comes out the other end of these algorithms.