  The modern age has seen an exponential growth of social network data
available on the web. Analysis of these networks reveal important structural
information about these networks in particular and about our societies in
general. More often than not, analysis of these networks is concerned in
identifying similarities among social networks and how they are different from
other networks such as protein interaction networks, computer networks and food
web. In this paper, our objective is to perform a critical analysis of
different social networks using structural metrics in an effort to highlight
their similarities and differences. We use five different social network
datasets which are contextually and semantically different from each other. We
then analyze these networks using a number of different network statistics and
metrics. Our results show that although these social networks have been
constructed from different contexts, they are structurally similar. We also
review the snowball sampling method and show its vulnerability against
different network metrics.
