Slashdot Mirror
AIM Meets Social Network Theory
dan moore writes "A student at Caltech has created a website (BuddyZoo.com) that tracks cliques within groups of peoples' buddylists. It also measures buddy popularity and allows you to do a six-degrees type search for other screen names. An interesting approach to social network theory."
now you can find out with all certainty if you are the lamest and most unpopular person on the Internet.
-Look lively. LOOK LIVELY!!! --Mr. Shmallow
Sheez, some people collect IM buddies as a sport. You'd think someone has no real friends in life with 373 buddies in his contact list.
There are several websites out there that track LiveJournal friends lists and allow you to see how many steps away you are from people, who is in your immediate circle, and other features. They're also a lot more complete, since I believe they gain the friends data by scraping the user info pages of people, instead of each person having to sign up and upload a list of all their friends.
Also, LiveJournal has a few features built directly into the site that do somewhat similar things. You can get a list of friends who are popular with your own friends, and a listing of all the most recent posts of your friends' friends.
A couple of things
m l
I don't have the data already. Users contribute their lists to the site by uploading them.
I'm not going to spam people. I promise.
This load makes me glad I put the time into setting up mod_perl
proof that I made the site:
http://www.buddyzoo.com/images/slashdot.ht
Feeling up to it, cmdrtaco?
Maybe someone who's not an editor can do it too, if they can spider all the user pages. But I suspect it would take forever to do it without getting your IP banned.
I once came across a list of all /. users up to 5 levels in the friends chain from Cmdrtaco (i.e, friends of cmdrtaco, friends of friends, ...). I tried googling it now but can't seem to find it :(
Much like my email address, the less people know about it, the better.
The less people I know on AIM will effectively minimize my chances of existing on that site.
Unpopularity pays off here.
This can help out AIM in an undirect way. AIM spammers spam the living hell out of all members on that site. Users cannot set higher privacy settings (in chance of losing chances meeting new people and such), they can't have effective spam filters like spam killer for email. The spam is even more direct, it's not sitting in your mailbox, it's DIRECTLY on your desktop. Users find new IM screen names. AOL claims their AIM program is more popular due to the new 10 million users, who basically might be the same 10 million highschool/college kiddies.
Technical:
It is a bit interesting, actually. I just wonder when his program will collapse, what the upper limit of number of users are.
I mean, this is a classical data-mining problem.
Philosophical / Paranoia:
When techniques like these functional enough to really work on large amounts of users, it's going to be candy for Big Brother.
They can just look at the graph over the people doing unwanted stuff and remove the spiders of those webs (the leaders of those underground networks). I think this is a great example of how important it is for us to develop freenet techniques.
Hofstadter's Law: It always takes longer than you expect, even if you take into account Hofstadter's Law