On the Correlation between Research Performance and Social Network Analysis Measures Applied to Research Collaboration Networks

Alireza Abbasi and Jörn Altmann

No 201066, TEMEP Discussion Papers from Seoul National University; Technology Management, Economics, and Policy Program (TEMEP)

Abstract: In this study, we develop a theoretical model based on social network theory to understand how the collaboration (co-authorship) network of scholars correlates to the research performance of scholars. For this analysis, we use social network analysis (SNA) measures (i.e., normalized closeness centrality, normalized betweenness centrality, efficiency, and two types of degree centrality). The analysis of data shows that the research performance of scholars is positively correlated with two SNA measures (i.e., weighted degree centrality and efficiency). In particular, scholars with strong ties (i.e., repeated co-authorships, i.e., high weighted degree centrality) show a better research performance than those with low ties (e.g., single co-authorships with many different scholars). The results related to efficiency show that scholars, who maintain a strong co-authorship relationship to only one co-author of a group of linked co-authors (i.e., co-authors that have joined publications), perform better than those researchers with many relationships to the same group of linked co-authors.

Keywords: Social Network Analysis; Co-authorship Network; Researchers' Performance. (search for similar items in EconPapers)
JEL-codes: C43 C44 C65 D80 D85 M12 M21 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2010-10, Revised 2010-10
New Economics Papers: this item is included in nep-ino, nep-ipr, nep-pr~, nep-net, nep-soc, nep-sog and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Published in Hicss44, Hawaii International Conference on System Sciences, January 2011

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Persistent link: https://EconPapers.repec.org/RePEc:snv:dp2009:201066

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