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The modern age has seen an exponential growth of social network dataavailable on the web. Analysis of these networks reveal important structuralinformation about these networks in particular and about our societies ingeneral. More often than not, analysis of these networks is concerned inidentifying similarities among social networks and how they are different fromother networks such as protein interaction networks, computer networks and foodweb. In this paper, our objective is to perform a critical analysis ofdifferent social networks using structural metrics in an effort to highlighttheir similarities and differences. We use five different social networkdatasets which are contextually and semantically different from each other. Wethen analyze these networks using a number of different network statistics andmetrics. Our results show that although these social networks have beenconstructed from different contexts, they are structurally similar. We alsoreview the snowball sampling method and show its vulnerability againstdifferent network metrics.

Are all Social Networks Structurally Similar? A Comparative Study using Network Statistics and Metrics