Almost anything you care to measure about weblogs -- number of inbound links, number of outbound links, posts per day, number of readers, number of writers -- follows the power law distribution. Millions of weblogs have only a few inbound links; and vice versa. Plot log(rank order) against log(your measure), you'll see a straight line.

Unlike, say, a plot of population height (something like a bell curve, with a clear mean value), these are scale-free networks. There's no typical number. In some ways they are self-similar at wildly different scales.

The same is true of webpages in general, as Barabási's research team discovered several years ago. It's also true of the physical infrastructure of the Net: bandwidth per link, or links per router. And our social connections (number of acquaintances, number of co-workers, number of sexual partners, etc) and of many other systems. It seems that scale-free topologies are an inherent result of the way some networks grow: incrementally adding links, with "preferential attachment" meaning that links in the network are created not simply at random, or only bounded by distance, but that big often begets bigger.

In Linked, Barabási takes a journey through the very recent discovery of these scale-free systems, and unfolds the story of the models to explain their existence, their formation, and their dynamics. It's developed at a gentle enough pace that Dylan's always half a step ahead ("Dad - this can't be right!" - "Yes, I know, you have to read the next chapter to find out why!"), but narrated with nicely diverse examples of why this stuff matters.

At the end of the book, after some discussion how how networks fail (and how they can be made to fail), it's clear that the dynamics of network growth are still largely unexplored. This isn't Crossing the Chasm or The Tipping Point yet, but it's just as important if you're exploring how {markets, groups, organizations} work.