Evaluating the power of homophily and graph properties in Social Network: Measuring the flow of inspiring influence using evolutionary dynamics

Interaction with different person leads to different kinds of ideas and sharing or some nourishing effects which might influence others to believe or trust or even join some association and subsequently become the member of that community. This will facilitate to enjoy all kinds of social privileges. These concepts of grouping similar objects can be experienced as well as could be implemented on any Social Networks. The concept of homophily could assist to design the affiliation graph (of similar and close similar entities) of every member of any social network thus identifying the most popular community. This paper will propose and discuss a novel data-mining algorithm from the perspective of graph properties (embeddedness, betweenness and graph occupancy) of a social network. A novel contribution has been made in the proposal while incorporating principle of evolutionary dynamics to investigate the graph properties. The prime objective is to authenticate the results of homophily identification for social network instance(s). Finally, the implication of homophily graph for cultivating leading community of social network has also been solicited.