Rank Consensus Between Importance Measures in Hypergraph Model of Social Network

Abstract

In social network (SN), a node is considered as a social entity and a link defines the connection between social entities. In general, the link is shown as a dyadic relationship which is unable to represent a group having super-dyadic relationship. Hypergraph model of a network preserves the super-dyadic relation between the nodes. Several algorithms have been developed to measure the node importance and ranking the nodes according to importance. Some measures take less time, whereas some take more time. We propose a method to find the correlation between the different importance measures in hypergraph. By establishing high correlation, the ranking of a time inefficient importance measure can be computed from a time-efficient measure. In this paper, we present our contribution in twofold. At first, we show the construction of primal/Gaifman graph from hypergraph. Secondly, we establish the correlation between the different importance measures that are used for ranking the nodes of a hypergraph.