It incorporates two important general concepts: growth and preferential attachment.

Both growth and preferential attachment exist widely in real networks.

Intuitively, the preferential attachment can be understood if we think in terms of social networks connecting people.

Model A retains growth but does not include preferential attachment.

So preferential attachment alone is not sufficient to produce a scale-free structure.

The principal reason for scientific interest in preferential attachment is that it can, under suitable circumstances, generate power law distributions.

The first application of preferential attachment to learned citations was given by Price in 1976.

This type of scenario is often termed a preferential attachment (or "rich get richer") model.

We assume that the network evolves through a modified preferential attachment mechanism.

This was later called the Yule process, but is now better known as preferential attachment.