An Evolving Scale-free Network with Large Clustering Coefficient

Preferential attachment is generally regarded as the best mechanism to form scale-free networks. However, the simulated network has a much smaller clustering coefficient, while many networks in the real world, such as movie actors´ collaboration and co-authorship networks, have a high clustering coefficient. So we develop the relatively preferential attachment (RPA) method which considers preferential attachment as well as the probability channel. RPA model can produce networks which not only keep the scale free property but also have high clustering coefficient close to those of real networks