An ANP-based method for modeling centrality in Online Social Networks

Abstract

The use of Centrality Measures (CMs) in the analysis of Online Social Networks (OSNs) has proved to be an effective strategy for identification of potentially influential users who can disseminate information on the network faster and more efficiently. Nevertheless, the selection based on individual CMs focuses in a particular user's attribute that singly may not reflect its real importance. In this sense, this paper presents a multicriterial approach for analyzing centrality in OSNs by using the Analytic Network Process (ANP) method, which are modeled by means of the interrelationships between CMs to provide greater robustness in the central user's selection. A set of simulations was also performed, showing the consistency and good performance of the proposed method.