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Functional information characteristics of large-scale research collaboration: network measures and implications

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Abstract

This exploratory work sheds light on important functional information characteristics of the system of research collaboration by examining large-scale topological structures of co-authorship networks, created through the affiliative ties of scholarly articles published by collaborating researchers in peer-reviewed journals and conference proceedings. The model adopted in this work to understand the underlying collaboration system incorporates the strengths of collaborative coupling among the researchers. The questions we examine in this work are as follows: (1) What new functional characteristics emerge when combined structural effects of collaborative coupling and large-scale connectivity exist in the networks? (2) What information does a specific closeness distribution of collaborating researchers convey with regard to the flow of knowledge through collaborative activities? (3) What is the temporal dynamics of large-scale structure formation in these networks? The work involves a comparative study of these characteristics using the networks of two countries: India and the US. Our results have important implications for scientometric studies of collaboration research.

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Notes

  1. We used the subject category Business Management and Accounting for Scopus. For WoS, we used the category operations research, management science, management, economics, business, and business finance.

  2. The selection of the time window was not motivated by any financial or political events in the US or in India. The time horizon of this study was a period when the MGMT field was actively growing in both countries. We did retrieve some earlier data (from the 80s and the 90s), but they turned out to be either incomplete in indexing or insufficient in volume in either one or the other of the databases to provide reliable statistical estimates of the quantities of interest in this study.

  3. A giant cluster of researchers is a connected cluster containing the largest number of researchers in the network. Commonly, it is called giant, when the concerned network operates in the percolating regime (Newman 2001a).

  4. There may be more than one of these.

  5. Still shorter periods using data over 4 or 6 months are theoretically possible, but the journal listings in the actual databases are incompletely indexed over such short periods.

  6. We thank a reviewer for raising this point.

  7. The Epanechnikov kernel is used to compute the density (Greene 2002).

  8. Many senior researchers are also known to quit research in order to accept administrative roles.

  9. Such a section has both high transitivity as well as a large coupling strength.

  10. Interestingly, a disparity analysis has been used to identify some dominant reactions in metabolic networks (Almaas et al. 2004).

  11. We thank a reviewer for raising this interesting question regarding the merging of the two datasets created from two separate databases. Unfortunately, we have not encountered any references in the literature where this has actually been performed in the network construction process.

  12. We thank a reviewer for pointing it out to us.

  13. We thank a reviewer for raising this point.

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Acknowledgments

The authors wish to acknowledge three anonymous reviewers of Scientometrics for suggesting a number of improvements in the paper. Thanks are also due to Dr. P. Banerjee, Director of CSIR–NISTADS, for helpful comments on an early version of the paper. Jaideep Ghosh would like to thank the Department of Science & Technology, Government of India, for financial support to carry out this work.

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Authors and Affiliations

  1. Council of Scientific and Industrial Research–National Institute of Science, Technology and Development Studies (CSIR–NISTADS), K. S. Krishnan Marg, PUSA Gate, New Delhi, 110012, India

    Jaideep Ghosh, Avinash Kshitij & Sandeep Kadyan

  2. Centre for Studies in Science Policy, School of Social Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Avinash Kshitij

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  1. Jaideep Ghosh
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Correspondence to Jaideep Ghosh.

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Ghosh, J., Kshitij, A. & Kadyan, S. Functional information characteristics of large-scale research collaboration: network measures and implications. Scientometrics 102, 1207–1239 (2015). https://doi.org/10.1007/s11192-014-1475-4

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