Degree of Diffusion in Real Complex Networks

A measure of information diffusion in real complex networks is the degree of diffusion. In this work, we assess the effect of information diffusion of seven different directed and undirected real complex networks and for several undirected generated networks; random, small world, and scale-free networks. The degree of diffusion α has been used to measure the diffusion and the adoption rates of different complex networks. It is defined as the percentage between the adopters and non-adopters in a network during the diffusion process. The results showed that the degree of diffusion α of undirected networks is different than directed networks. All the obtained results showed that in real networks, randomization does not exist. The behavior of these networks is determined based on the network's members and the interactions between them. Therefore, most of the real networks should be classified as small-world, scale-free networks, or what we defined as small-world random, small-world scalefree networks.