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Identifying the Effects of Co-Authorship Networks on the Performance of Scholars: A Correlation and Regression Analysis of Performance Measures and Social Network Analysis Measures

  • Alireza Abbasi
  • Jorn Altmann

    ()

    (Technology Management, Economics, and Policy, College of Engineering, Seoul National University)

  • Liaquat Hossain

In this study, we develop a theoretical model based on social network theories and analytical methods for exploring collaboration (co-authorship) networks of scholars. We use measures from social network analysis (SNA) (i.e., normalized degree centrality, normalized closeness centrality, normalized betweenness centrality, normalized eigenvector centrality, average ties strength, and efficiency) for examining the effect of social networks on the (citation-based) performance of scholars in a given discipline (i.e., information systems). Results from our statistical analysis using a Poisson regression model suggest that research performance of scholars (g-index) is positively correlated with four SNA measures except for the normalized betweenness centrality and the normalized closeness centrality measures. Furthermore, it reveals that only normalized degree centrality, efficiency, and average ties strength have a positive significant influence on the g-index (as a performance measure). The normalized eigenvector centrality has a negative significant influence on the g-index. Based on these results, we can imply that scholars, who are connected to many distinct scholars, have a better citation-based performance (g-index) than scholars with fewer connections. Additionally, scholars with large average ties strengths (i.e., repeated co-authorships) show a better research performance than those with low tie strengths (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, perform better than those researchers with many relationships to the same group of linked co-authors. The negative effect of the normalized eigenvector suggests that scholars should work with many students instead of other well-performing scholars. Consequently, we can state that the professional social network of researchers can be used to predict the future performance of researchers.

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File URL: ftp://147.46.237.98/DP-76.pdf
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Paper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 201176.

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Length: 31 pages
Date of creation: Jun 2011
Date of revision: Jun 2011
Publication status: Published in Journal of Informetrics
Handle: RePEc:snv:dp2009:201176
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  1. Owen-Smith, Jason & Riccaboni, Massimo & Pammolli, Fabio & Powell, Walter W., 2002. "A Comparison of U.S. and European University-Industry Relations in the Life Sciences," MPRA Paper 15963, University Library of Munich, Germany.
  2. Richard S.J. Tol, 2007. "A Rational, Successive G-Index Applied To Economics Departments In Ireland," Working Papers FNU-147, Research unit Sustainability and Global Change, Hamburg University, revised Sep 2007.
  3. Jorn Altmann & Alireza Abbasi & Junseok Hwang, 2010. "Evaluating the Productivity of Researchers and their Communities: The RP-Index and the CP-Index," TEMEP Discussion Papers 201048, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.
  4. Frances Ruane & Richard S.J. Tol, 2007. "Refined (Successive) H-Indices: An Application To Economics In The Republic Of Ireland," Working Papers FNU-130, Research unit Sustainability and Global Change, Hamburg University, revised Mar 2007.
  5. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
  6. Linton Freeman, 1980. "The gatekeeper, pair-dependency and structural centrality," Quality & Quantity: International Journal of Methodology, Springer, vol. 14(4), pages 585-592, August.
  7. Gibbons, Michael R., 1982. "Multivariate tests of financial models : A new approach," Journal of Financial Economics, Elsevier, vol. 10(1), pages 3-27, March.
  8. Melin, Goran, 2000. "Pragmatism and self-organization: Research collaboration on the individual level," Research Policy, Elsevier, vol. 29(1), pages 31-40, January.
  9. Alireza Abbasi & Jorn Altmann, 2010. "A Social Network System for Analyzing Publication Activities of Researchers," TEMEP Discussion Papers 201058, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Apr 2010.
  10. Alireza Abbasi & Jorn Altmann & Junseok Hwang, 2009. "Evaluating Scholars Based on their Academic Collaboration Activities: The RC-Index and CC-Index for Quantifying Collaboration Activities of Researchers and Scientific Communities," TEMEP Discussion Papers 200915, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2009.
  11. Kibae Kim & Jorn Altmann & Junseok Hwang, 2010. "Measuring and Analyzing the Openness of the Web2.0 Service Network for Improving the Innovation Capacity of the Web2.0 System through Collective Intelligence," TEMEP Discussion Papers 201057, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Mar 2010.
  12. Daniel Z. Levin & Rob Cross, 2004. "The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer," Management Science, INFORMS, vol. 50(11), pages 1477-1490, November.
  13. Alireza Abbasi & Jorn Altmann, 2010. "On the Correlation between Research Performance and Social Network Analysis Measures Applied to Research Collaboration Networks," TEMEP Discussion Papers 201066, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2010.
  14. Harold Guetzkow & Herbert A. Simon, 1955. "The Impact of Certain Communication Nets Upon Organization and Performance in Task-Oriented Groups," Management Science, INFORMS, vol. 1(3-4), pages 233-250, 04-07.
  15. Wagner, Caroline S. & Leydesdorff, Loet, 2005. "Network structure, self-organization, and the growth of international collaboration in science," Research Policy, Elsevier, vol. 34(10), pages 1608-1618, December.
  16. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer, vol. 31(4), pages 581-603, December.
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