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On the relationship between the structural and socioacademic communities of a coauthorship network

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  • Rodriguez, Marko A.
  • Pepe, Alberto

Abstract

This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of a multi-institution, interdisciplinary research group focused on the study of sensor networks and wireless communication. Four different community detection algorithms were employed to assign a structural community to each scholar in the network: leading eigenvector, walktrap, edge betweenness and spinglass. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic affiliation, country of origin, and academic position. A Pearson’s χ2test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result suggests that, even in interdisciplinary, multi-institutional research groups, coauthorship is primarily driven by departmental and institutional affiliation.

Suggested Citation

  • Rodriguez, Marko A. & Pepe, Alberto, 2008. "On the relationship between the structural and socioacademic communities of a coauthorship network," Journal of Informetrics, Elsevier, vol. 2(3), pages 195-201.
    • Handle: RePEc:eee:infome:v:2:y:2008:i:3:p:195-201
    DOI: 10.1016/j.joi.2008.04.002
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    Cited by:

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    21. Yan, Xiangbin & Zhai, Li & Fan, Weiguo, 2013. "C-index: A weighted network node centrality measure for collaboration competence," Journal of Informetrics, Elsevier, vol. 7(1), pages 223-239.

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