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https://www.arca.fiocruz.br/handle/icict/31005
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2019-01-01
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NETWORK ANALYSIS TO SUPPORT PUBLIC HEALTH: EVOLUTION OF COLLABORATION AMONG LEISHMANIASIS RESEARCHERS
Affilliation
Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / National Institute for Science and Technology on Innovation on Neglected Diseases. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Diretoria Regional de Brasilia. Brasilia, DF, Brasil.
Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / National Institute for Science and Technology on Innovation on Neglected Diseases. Rio de Janeiro, RJ, Brazil
Rensselaer Polytechnic Institute. Computer Science.Troy, NY, USA.
Rensselaer Polytechnic Institute. Computer Science.Troy, NY, USA / Spoleczna Akademia Nauk. Lodz, Poland.
Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / National Institute for Science and Technology on Innovation on Neglected Diseases. Rio de Janeiro, RJ, Brazil
Rensselaer Polytechnic Institute. Computer Science.Troy, NY, USA.
Rensselaer Polytechnic Institute. Computer Science.Troy, NY, USA / Spoleczna Akademia Nauk. Lodz, Poland.
Abstract
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 ollaboration between different research groups within a specific research area and that those areas have subnetworks that influence collaboration structures and focus.
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