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Book review: Darwinia
Reviewed: Friday, August 11, 2006

Summer reading: Spin
Reviewed: Saturday, August 5, 2006

Reviewed: Tuesday, July 18, 2006

the Omnivoire's Delimma
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the Golem's Eye
Reviewed: Wednesday, May 31, 2006


Growing scale-free networks with tunable clustering
Petter Holme and Beom Jun Kim, 2002 , (Paper URL)
Tuesday, November 1, 2005

This is yet another network generation paper. As you may recall, the Barabasi-Albert model provides scale-free distributions of the vertex degree (i.e., it's a power law: a few vertexes have a huge number of edges, lots of vertexes have many edges and bazillions of vertexes have just a few edges) and the Watts Strogatz model gives high clustering coefficients (friends of my friends are also often friends) but neither gives both.

Here, Holme and Kim start with the Barabasi-Albert model and add a new triad-formingstep. This makes sense: if you the want the final graph to have more triples, then ensure that more triples are added during graph generation! The exciting thing is that not only do you get the triples (and therefore a tunable clustering coefficient) but you still get the power-law degree distribution.

The analysis in this paper is relatively light-weight but I actually enjoyed that (I'm a computer scientist (heh, heh), not a statistical physicist). It takes a nice idea, elaborates it, shows that it works and wraps it up. Nice.

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