Towards validating social network simulations

Abstract

We consider the problem of finding suitable measures to validate simulated networks as outcome of (agent-based) social simulations. A number of techniques from computer science and social sciences are reviewed in this paper, which tries to compare and 'fit' various simulated networks to the available data by using network measures. We look at several social network analysis measures but then turn our focus to techniques that not only consider the position of the nodes but also their characteristics and their tendency to cluster with other nodes in the network - subgroup identification. We discuss how static and dynamic nature of networks may be compared. We conclude by urging a more comprehensive, transparent and rigorous approach to comparing simulation-generated networks against the available data. © Springer-Verlag Berlin Heidelberg 2014.