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

Geraldo J. Pessoa Junior (), Thiago M. R. Dias (), Thiago H. P. Silva () and Alberto H. F. Laender ()
Additional contact information
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

Scientometrics, 2020, vol. 124, issue 3, No 26, 2360 pages

Abstract: 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.

Keywords: Interdisciplinary collaborations; Coauthorship networks; Scientific communities; Lattes Platform (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-020-03605-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:124:y:2020:i:3:d:10.1007_s11192-020-03605-3

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-020-03605-3

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().