Databases on scientific publications are a well-known source for complex network analysis. The present work focuses on tracking evolution of collaboration
amongst researchers on leishmaniasis, a neglected disease associated with poverty and very common in Brazil, India and many other countries in Latin America, Asia and
Africa. Using SCOPUS and PubMed databases we have identified clusters of publications resulting from research areas and collaboration between countries. Based
on the collaboration patterns, areas of research and their evolution over the past 35 years, we combined different methods in order to understand evolution in science. The
methods took into consideration descriptive network analysis combined with lexical analysis of publications, and the collaboration patterns represented by links in network
structure. The methods used country of the authors’ publications, MeSH terms, and the collaboration patterns in seven five-year period collaboration network and publication
networks snapshots as attributes. The results show that network analysis metrics can bring evidences of evolution of collaboration between different research groups within a
specific research area and that those areas have subnetworks that influence collaboration structures and focus.
https://link.springer.com/article/10.1007%2Fs11192-017-2346-6
For full-text, https://pdfs.semanticscholar.org/ec2d/72caf565d297db3699953c9eceea25c81b17.pdf
Author(s): Ricardo B. Sampaio, Bruna P.F. Fonseca, Ashwin Bahulkar, Boleslaw K.
Szymanski
Organization(s): Oswaldo Cruz Foundation (Fiocruz), Rensselaer Polytechnic Institute, Społeczna Akademia Nauk
Source: Scientometrics
Year: 2017