A survay on centrality measure in co-authorship networks in information science journals

Document Type : Research Article

Authors

Professor of the library department of Shahid Chamran University of Ahvaz

Abstract

Purpose: The present study aims to investigate the centrality measure in co-authorship social networks in journals of information science indexed by Thompson Reuters database.

Method: The present study was carried out using network analysis. The research population consisted of all information science journals which had the impact factors more than 0.6.

Findings: The results showed that Gelnzen had the highest degree, betweeness, closeness and eigenvector centrality in the Sciencetometrics journal while Nicols had the highest degree, eigenvector and Beta centrality in information science journal. The findings indicated that information science researchers' co-authorship social network generally had a low density and a low centrality measure compared to other scientific fields.

Keywords


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