Network models

A network model is a method to generate artificial networks. When implemented in software, a network model can be used in simulations and experiments.

The random model, also known as Erdős-Rényi model, is simplest and oldest network model. According to this model, a network is generated by laying down a number $n$ of nodes and adding edges between them with independent probability $p$ for each node pair. It is implemented in igraph with function sample_gnp. A random graph with $n = 100$ nodes and probability $p = 2/100$ is shown in the following:

An alternative is the preferential attachment model, also known as Barabasi-Albert model. Such a model works as follows:

1. The $n$ nodes are added to the network one at a time.
2. Each node connects to the existing nodes with a fixed number $m$ of links. The probability that it will choose a given node is proportional to the degree of the chosen node.