The joy of Albert-László Barabási's book, Linked: The New Science ofNetworks is that, after reading it, you can't look anywhere withoutseeing networks. The book, which is currently ranked 99th on Amazon's topseller's list, leaves a powerful imprint on the mind's eye.
Did you realize that it takes an average of only one link per node tobind together a random conglomeration of 100 nodes into a seamless network?No wonder gossip travels so fast.
But although most laymen and scientists imagine a "classic network" to be arandom and evenly distributed mesh of linkages among nodes, Barabásiillustrates that many key networks are, in fact, severely uneven. In thesenetworks, called "scale-free," most nodes have only a few links, while a fewnodes have lots.
Obviously, to anyone who looks at their own social network, the scale-freemodel doesn't seem radical. We take for granted that our neighbor Howard isin close touch with 100s of people while most people, like his wife Susie,talk to the same 35 people year in and year out.
What astonishes, however, is that nearly every network we know — whetherit is the network of a cell's molecules, Hollywood, the Internet,Yellowstone's ecosystem, or the "sex map" of patients suffering AIDS — ispopulated almost entirely by Franks and Susies. None of these networksconform to the classically imagined "random" model. All these arefree-scale networks. All rely on a few hyperlinkers to do the bulk of theirwork, whether that work is communicating, making movies, eating rodents, orpassing on disease. Moreover, these uneven networks display distinct andrecurring distributions of high-linkage versus low-linkage nodes.
The scale-free network's linkage distribution has important byproducts. Likethe "classic" random network, scale-free networks are amazingly efficient atdistributing information. Unlike their random cousins, scale-free networksare practically immune to the random failure of individual nodes — nearlyall nodes can be eliminated and the network survives.