Key Author Analysis in Research Professionals' Collaboration Network based on MST using Centrality Measures

Abstract

The importance of an actor in the network is measured by the different type of centrality metrics of Social Network Analysis (SNA). In the research community, who are the most prominent author or key on the network is the major discussion or research issue. Different types of centrality measures and citation based indices are available, but their result is varied from network to network. In this paper, we form a network of author and its co-author based on Maximum Spanning Tree and find out the key author based on social network analysis metrics like degree centrality, closeness centrality, betweenness centrality and eigenvector centrality. After that we compare the result of all centrality measures of MST based network and original network, betweenness centrality value increases and the other centrality value decreases. Finally, we conclude that the betweenness centrality is useful to analyze key author in this type of network.

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