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Visualizing cooperation networks of elite institutions in India

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  • P. S. Nagpaul

    (National Institute of Science)

Abstract

In this paper we have analyzed the pattern of cooperation links among fifty most prolific institutions (hereafter called “elite institutions”) in India. The network of relationships among these institutions is sparse and more than two thirds of the cells in the collaboration matrix are empty. The network is centralized, but no institution dominates the network. It is only a set of few institutions that dominate the network. We have constructed a measure (Bonacich eigenvector centrality index) to assess the position of each institution in the network. Barring a few notable exceptions, scientific size of an institution is directly related to its position in the network. We have graphically depicted the network of relationships among these institutions above a certain threshold of cooperation strength. The network incorporating 50 nodes and 171 arcs provides a synoptic view of bilateral relations among the institutions, but it is quite complex. We have therefore developed a block model of the network to assess the macro level features of cooperation links among the institutions. The block model indicates the isolation and marginality of certain clusters (or blocks) of institutions.

Suggested Citation

  • P. S. Nagpaul, 2002. "Visualizing cooperation networks of elite institutions in India," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 213-228, June.
  • Handle: RePEc:spr:scient:v:54:y:2002:i:2:d:10.1023_a:1016036711279
    DOI: 10.1023/A:1016036711279
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    Cited by:

    1. Liying Yang & Steven A. Morris & Elizabeth M. Barden, 2009. "Mapping institutions and their weak ties in a specialty: A case study of cystic fibrosis body composition research," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(2), pages 421-434, May.
    2. Gohar Feroz Khan & Junghoon Moon & Han Woo Park, 2011. "Network of the core: mapping and visualizing the core of scientific domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 759-779, December.
    3. Zhao, Star X. & Ye, Fred Y., 2012. "Exploring the directed h-degree in directed weighted networks," Journal of Informetrics, Elsevier, vol. 6(4), pages 619-630.
    4. Giulia Rivellini & Ester Rizzi & Susanna Zaccarin, 2006. "The science network in Italian population research: An analysis according to the social network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 407-418, June.
    5. Sergey Shashnov & Maxim Kotsemir, 2018. "Research landscape of the BRICS countries: current trends in research output, thematic structures of publications, and the relative influence of partners," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1115-1155, November.
    6. Nuha Zamzami & Andrea Schiffauerova, 2017. "The impact of individual collaborative activities on knowledge creation and transmission," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1385-1413, June.
    7. Gohar Feroz Khan, 2013. "Social media-based systems: an emerging area of information systems research and practice," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 159-180, April.
    8. Ortega, José Luis & Aguillo, Isidro F., 2013. "Institutional and country collaboration in an online service of scientific profiles: Google Scholar Citations," Journal of Informetrics, Elsevier, vol. 7(2), pages 394-403.
    9. Kamal Badar & Julie M. Hite & Yuosre F. Badir, 2013. "Examining the relationship of co-authorship network centrality and gender on academic research performance: the case of chemistry researchers in Pakistan," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 755-775, February.
    10. Kamal Badar & Julie M. Hite & Naeem Ashraf, 2015. "Knowledge network centrality, formal rank and research performance: evidence for curvilinear and interaction effects," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1553-1576, December.

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