The secret physics of social network growth

A crowd draws a crowd but you need to be fit too. Distinguished Physicist Albert Laszlo Barabasi in his excellent book "Linked - the New Science of Networks" lets us into the secret of how any kind of network grows.


Relatively new research has shown that most networks are not random, as previously thought, but "Scale Free" .

New nodes in a scale free networks attach themselves to other nodes based on a "preferrential attachment rule" .

So the probability of a new member joining your network depends on the product of two factors known as the fitness connectivity product:

The number of existing members already linked into your network

multiplied by

The potential new member's assessment of the "fitness" of your network

Albert goes on to show that there are two network growth scenarios.

In Fit-get-rich there will be many winners.

These will be the fittest networks and each of the winners will have many more linked nodes than the losing networks (according to a Power Law).

in Winner-takes-all there will be only one winner - a single network which ends up with almost all the nodes linked to them.

Barabasi offers lots of examples of Fit-get-rich scenarios but says that the only real example of Winner-takes-all is Microsoft Windows!

Its also worth a visit to the books excellent companion web-site.

Buy it now from:

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can the Winner-takes-all also apply to a 'digital life aggregator'? what if a program comes around that is like an RSS reader for social networks. i used to go look at individual sites all the time and the fittest would get the most traffic. Now with an RSS reader, I scan for information and my attention is relatively evenly distributed with a few sources getting particular attention, but still through the RSS reader.

would a "digital life aggregator" that was the uber controller and interface with your networks, fit in the Winner-takes-all category?

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