The self-similarity of complex networks: From the view of degree–degree distance

Abstract

Self-similarity of complex networks has been discovered and attracted much attention. However, the self-similarity of complex networks was measured by the classical distance of nodes. Recently, a new feature, which is named as degree–degree distance, is used to measure the distance of nodes. In the definition of degree–degree distance, the relationship between two nodes is dependent on degree of nodes. In this paper, we explore the self-similarity of complex networks from the perspective of degree–degree distance. A box-covering algorithm based on degree–degree distance is proposed to calculate the value of dimension of complex networks. Some complex networks are studied, and the results show that these networks have self-similarity from the perspective of degree–degree distance. The proposed method for measuring self-similarity of complex networks is reasonable.