Statistical properties of model kinship networks

Abstract

We report on the statistical characterization of a class of networks representing kinship in a model for a human population of men and women who form heterosexual monogamous married couples. Specifically, networks are built from blood and in-law sibling connections within the same generation, for either gender. The distribution of the number of blood siblings of each individual is controlled by a randomness parameter, and the only condition imposed on marriages is avoidance of brother-sister mating. By means of numerical simulations of the population, we analyze the statistics of the number and size of connected components, properties of the degree distribution, clustering, assortativity, and distances inside the giant component. To emphasize structural peculiarities of kinship networks, in all cases, we compare with random networks with the same degree distribution. Kinship networks exhibit a nontrivial coexistence of distinctive traits—such as high clustering and assortativity—and features which are typical of random networks.