AN ANALYSIS OF LINK STRENGTH IN SOCIAL NETWORKS

Abstract

A social structure made of nodes that are generally individuals or organizations. A social network represents relationships and flows between people, groups, organizations, animals, computers or other information or knowledge processing entities. Social networking websites allow users to be part of a virtual community. Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Link prediction in Facebook and Twitter can be done at a familiar class of graph generation model, where the nodes are united with locations in a latent metric space and connections are most likely between closer nodes. In this paper, GEPHI and NODEXL tools are used for the comparison measures to predict betweenness centrality of particular users account in Facebook and Twitter.