Metrics of social websites: A case study

Social Networks are the common platform for the present generations to share ideas. The members of these sites have grown to billions in the last decade and much more at present. In this paper, the metrics Page Rank, Path Length, Clustering Coefficient and Vertex Degree for SNWSs are evaluated by users´ database of Facebook. The results indicate that the metrics Page Ranking, Path Length and Vertex Degree first three and last hold highest values and form an edge with the actors. The other metric Clustering Coefficient is reciprocal to the above metrics and the higher the value the greater isolation in the sub-group causing formation of Clique.