This paper mainly focuses on the development of quantitative approach based algorithm for comparing the social networks. Firstly, comparison of social networks can be done on different parameters at all the three levels – network, group and node level characteristics. Secondly, for getting more accurate results, the paper has incorporated weights to these parameters according to their importance. For addressing these two, the paper has taken an advantage from the Ordered Weighted Averaging (OWA) operator in the proposed algorithm. This algorithm outputs one quantitative value for each of the social network, on which the comparison has to be made. This paper has also employed the Gephi tool, in order to accomplish the quantitative and graphical comparison between the social networks. The analysis has been done on multiple varied social network data sets. This paper has made an effort to analyze, which among them is better in terms of connectivity and coherency factors. The paper takes into account six vital metrics of the social networks so that there will be low complexity with high accuracy. They are average degree, network diameter, graph density, modularity, clustering coefficient and average path length. The proposed SNA approach is very advantageous for finding the potential group suited for a particular task in different areas like identification of criminal activities, and more fields like economics, cyber security, medicine etc.