Rich get richer

From what I understand from the Barabasi reading, the sentence ‘rich get richer’ points to how a senior node is collectively gathering more links as time passes, compared to a new node that just joined the system, with only a few links. In his terms, real networks are governed by two laws, growth and preferential attachment. In 1999, 3.2 billion dollars were spent by small scale companies on online advertising alone. The reason? Trying to attract more links and hits to their website in lieu of the SuperBowl. As stated in my previous post, distribution of links per site follows a pareto style distribution.

According to the random network models, we would randomly link to any of the nodes.

Is it, really? An example here is when I search for ‘bpl (Barclays Premier League) updates’ in a search engine, my obvious choice would be ESPNfc.com because I am familiar with the channel. They more they are linked, the easier they are to find on the Web.

They are hubs. The better known they are, the more links point to them.

It is obvious people prefer hubs. It is true that it is an unnoticed bias. This is what Barabasi calls preferential attachment. He also goes against the Erdos-Renyi and Watts-Strogatz models where there is no difference between the nodes of a network, saying that “In real networks linking is never random”.

Network evolution is  governed by the subtle yet unforgiving law of preferential attachment.

So how does a node become a hub? Growth, seniority, and preferential attachment. Early nodes have more potential to gain links compared to the latecomers. Therefore, when they gain a lot of links they will eventually break off from the pack and form a hub. Using this simple observation, Barabasi was able to conclude in terms network topology, that the Web is indeed following a power law.

Also check out Tim’s post.