AN UPDATED LOOK AT SOCIAL NETWORK EXTRACTION SYSTEM A PERSONAL DATA ANALYSIS APPROACH

Abstract

With the rapid popularity of social networks, interactions between people are no longer limited to geographical boundaries. Social interactions between the different people are the basis for dynamic social networks. As a result of the interactions between different people they can influence one another. These interactions form the basis of community for e.g. scientific community. The communication between interconnected participants in a social network can be analysed and used to derive more information which can utilized in various ways. This paper studies the essential features of Facebook that is the friendship relation between participants and tries to find the influential user for a particular person. This has a huge impact on spreading new ideas and practises. In a marketing scenario the information is vital as identifying the influential person could be the turning point in sales promotion. As the dynamic network was studied over a period we could also analyze the structural changes in network that eventually changed the influential person. It is also observed that number of groups in the network tends to decrease as the size of network increases. Relationship is viewed in terms of network theory with actors as nodes and relation as links. An individual can bridge two networks that are not directly linked. The attributes of individual is less important than the relationship or ties with other nodes in and outside the network.