  The value of a social network is generally determined by its size and the
connectivity of its nodes. But since some of the nodes may be fake ones and
others that are dormant, the question of validating the node counts by
statistical tests becomes important. In this paper we propose the use of the
Benford's distribution to check on the trustworthiness of the connectivity
statistics. Our experiments using statistics of both symmetric and asymmetric
networks show that when the accumulation processes are random, the convergence
to Benford's law is significantly better, and therefore this fact can be used
to distinguish between processes which are randomly generated and those with
internal dependencies.
