Chinese character structure analysis based on complex networks

Abstract

In this paper, Chinese character networks are modelled using complex networks theory. We analyze statistical properties of the networks and find that character networks also display two important features as other real networks, i.e., small-world feature and the non-Poisson distribution. These results indicate that the discovered features of Chinese character structure reflect the combinatorial nature of Chinese characters. We also simulate the formation of Chinese phono-semantic characters using bipartite graph theory. The bipartite graph model generates non-Poisson distributions and disassortative mixing as the empirical networks, which effectively explain the origin and formation of phono-semantic characters.