HYPERGRAPH CENTRALITY METRICS FOR SOCIAL NETWORKS

There are numerous techniques exist for analyzing social and other networks. The centrality measures are one of the tools having an effective role, on that the degree and betweenness centrality measures play a vital role in identifying the influential nodes. These measures are crucial for adequately identifying prominent nodes, and recently, various techniques have been suggested. In this paper, we proposed algorithms for constructing a directed hypergraph, a hypergraph degree centrality, and a hypergraph betweenness centrality for social networks. The hypergraph degree centrality algorithm helps to determine the strong and weak ties of the network. The betweenness centrality algorithm for the directed hypergraph also aids in identifying the common and high-priority communication channels. We also calculated the number of hyperarcs for a directed hypergraph and validated it using various social networks like the Football game network, soc-wiki-Vote, so c-hamsterster, and so cfb-BU10.