Identification Power Nodes in Social Networks Using Data Mining

With the emergence of social networks، the relationships among people found a new horizon. Nowadays، a large number of users sign up in social networks with different goals and they get involved in different activities. On the other hand they affect on one another while their roles and effects are not the same. Some of these users have more effects on the others according to their job status، educational backgrounds and their attractive notes. These users، whom we call the power nodes، can change the perspective of many users and move them to specific directions. The aim of this research is the identification of the power nodes in Tebyan، as a social network، and such aim was fulfilled through a discovery of the concealed models in the characteristics of the users. This research has followed the standard methodology of CRISP-DM. To reach this end، after the identification of the power nodes، according to the attained sum scores، from three parameters: central relativity، the page rank، and the users activities، a classification was provided from an algorithm tree. The achieved results have shown that the most significant features in determination of a user''s power in a social network are education، age and gender.