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

Author

Listed:
  • Alireza Abbasi

    () (Technology Management, Economics, and Policy Program (TEMEP), Seoul National University)

  • Jorn Altmann

    () (Technology Management, Economics, and Policy Program (TEMEP), Seoul National University)

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.

Suggested Citation

  • 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.
  • Handle: RePEc:snv:dp2009:201066
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    File URL: ftp://147.46.237.98/DP-66.pdf
    File Function: First version, 2010
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    References listed on IDEAS

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    1. Jason Owen-Smith & Massimo Riccaboni & Fabio Pammolli & Walter W. Powell, 2002. "A Comparison of U.S. and European University-Industry Relations in the Life Sciences," Management Science, INFORMS, vol. 48(1), pages 24-43, January.
    2. Tol, Richard S.J., 2008. "A rational, successive g-index applied to economics departments in Ireland," Journal of Informetrics, Elsevier, vol. 2(2), pages 149-155.
    3. 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.
    4. 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.
    5. Kibae Kim & Jorn Altmann & Junseok Hwang, 2010. "An Analysis of the Openness of the Web2.0 Service Network Based on Two Sets of Indices for Measuring the Impact of Service Ownership," TEMEP Discussion Papers 201067, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2010.
    6. 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.
    7. 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.
    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. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    10. 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.
    11. 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.
    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.
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    Citations

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    Cited by:

    1. Krogmann, Yin & Riedel, Nadine & Schwalbe, Ulrich, 2013. "Inter-firm R&D networks in pharmaceutical biotechnology: What determines firm's centrality-based partnering capability," FZID Discussion Papers 75-2013, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    2. Abbasi, Alireza & Altmann, Jörn & Hossain, Liaquat, 2011. "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," Journal of Informetrics, Elsevier, vol. 5(4), pages 594-607.

    More about this item

    Keywords

    Social Network Analysis; Co-authorship Network; Researchers' Performance.;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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