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On interdisciplinary collaborations in scientific coauthorship networks: the case of the Brazilian community

Author

Listed:
  • Geraldo J. Pessoa Junior

    (Universidade Federal de Viçosa)

  • Thiago M. R. Dias

    (Centro Federal de Educação Tecnológica)

  • Thiago H. P. Silva

    (Universidade Federal de Minas Gerais)

  • Alberto H. F. Laender

    (Universidade Federal de Minas Gerais)

Abstract

Interdisciplinary collaborations have recently drawn the attention of scholars, since bridging academic relationships contributes to make scientific coauthorship networks stronger. However, previous studies have focused on characterizing specific groups rather than on studying a complete and robust scientific community. In this article, instead of analyzing particular scenarios, we characterize these collaborations with respect to the Brazilian scientific communities defined according to the upper level of a knowledge area classification scheme. For this, we collected data from the Lattes Platform, an internationally renowned initiative from CNPq, the Brazilian National Council for Scientific and Technological Development, that provides a repository of Brazilian researchers’ curricula vitae and research groups, all integrated into a single system. Our results show that the Brazilian coauthorship network grew and became especially interdisciplinary, with 35.2% of all collaborations being interdisciplinary and 57.6% of the researchers having participated in at least one interdisciplinary collaboration. We also investigate the intensity of these interdisciplinary collaborations across distinct communities. Finally, we explore a temporal view of the researchers’ career, thus identifying distinct collaboration patterns involving the aforementioned scientific communities.

Suggested Citation

  • Geraldo J. Pessoa Junior & Thiago M. R. Dias & Thiago H. P. Silva & Alberto H. F. Laender, 2020. "On interdisciplinary collaborations in scientific coauthorship networks: the case of the Brazilian community," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2341-2360, September.
    • Handle: RePEc:spr:scient:v:124:y:2020:i:3:d:10.1007_s11192-020-03605-3
    DOI: 10.1007/s11192-020-03605-3
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    References listed on IDEAS

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    1. Fernanda Morillo & María Bordons & Isabel Gómez, 2003. "Interdisciplinarity in science: A tentative typology of disciplines and research areas," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(13), pages 1237-1249, November.
    2. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2018. "The effect of multidisciplinary collaborations on research diversification," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 423-433, July.
    3. Loet Leydesdorff & Olle Persson, 2010. "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(8), pages 1622-1634, August.
    4. Shunshun Shi & Wenyu Zhang & Shuai Zhang & Jie Chen, 2018. "Does prestige dimension influence the interdisciplinary performance of scientific entities in knowledge flow? Evidence from the e-government field," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1237-1264, November.
    5. Jesús Pascual Mena-Chalco & Luciano Antonio Digiampietri & Fabrício Martins Lopes & Roberto Marcondes Cesar Junior, 2014. "Brazilian bibliometric coauthorship networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(7), pages 1424-1445, July.
    6. Maki Kato & Asao Ando, 2013. "The relationship between research performance and international collaboration in chemistry," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 535-553, December.
    7. Caio Alves Furtado & Clodoveu A Davis Jr. & Marcos André Gonçalves & Jussara Marques de Almeida, 2015. "A Spatiotemporal Analysis of Brazilian Science from the Perspective of Researchers’ Career Trajectories," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-28, October.
    8. Erjia Yan & Ying Ding & Cassidy R. Sugimoto, 2011. "P‐Rank: An indicator measuring prestige in heterogeneous scholarly networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(3), pages 467-477, March.
    9. Hajdeja Iglič & Patrick Doreian & Luka Kronegger & Anuška Ferligoj, 2017. "With whom do researchers collaborate and why?," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 153-174, July.
    10. Thiago H. P. Silva & Alberto H. F. Laender & Clodoveu A. Davis & Ana Paula Couto Silva & Mirella M. Moro, 2017. "A profile analysis of the top Brazilian Computer Science graduate programs," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 237-255, October.
    11. Erjia Yan & Ying Ding & Cassidy R. Sugimoto, 2011. "P-Rank: An indicator measuring prestige in heterogeneous scholarly networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(3), pages 467-477, March.
    12. Alan L Porter & David J Roessner & Anne E Heberger, 2008. "How interdisciplinary is a given body of research?," Research Evaluation, Oxford University Press, vol. 17(4), pages 273-282, December.
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    3. Francisco Galuppo Azevedo & Fabricio Murai, 2021. "Evaluating the state-of-the-art in mapping research spaces: A Brazilian case study," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-27, March.

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