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5th Assignment - Clusters

Twitter Network:
twitter1.jpg

It's not so easy to define clusters since there are persons that belong to several clusters at the same time and trying to define their proximity to one instead of another had to be a decision. In this network I found 4 big clusters: itp alumni + itp students + algorithm scene ( hard also to name this clusters - maybe " idols") + portugal ( mix communities). Also there were some persons that doesn't fit any cluster.
One important conclusion that I can take from this visualization is that media art organizations/institutes/groups ( most of them based in NY) are not interconnected, so they don't form a strong cluster or in other words, a big community!

links: Graph ML | Applet

Delicious Network:

delicious.jpg

I don't use del.ici.ous for a long time. Normally i make bookmarks in my computer browser. I think it was good exercise to reminder of such an amazing app delicious is
( even the name changed ?? - not more dotss) and an important resource to discover new things! In this network it's easier to define clusters, maybe because the network is smaller!

links: Graph ML | Applet

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This page contains a single entry from the blog posted on October 6, 2008 9:45 PM.

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