Análise de artigos científicos sobre COVID-19: uma perspectiva usando redes complexas

Abstract

The COVID-19 pandemic was one of the 21st century's biggest events, impacting the lives of all the people on the planet. From a scientific perspective, it was a very accelerated growth period for the medical, pharmaceutical and biochemistry areas, which developed research to fight the disease. In order to help the fight against the disease, scientific research groups compiled and made available a database containing articles of studies on COVID-19, SARS-CoV-2 and coronavirus, aiming to facilitate access to publications and the development of new research against the virus. From a computational perspective, we have different models to improve the visualization and analysis of datasets. One of these models is the complex networks, which describe their units (vertex) and relationships (edges) to help understand the behavior of complex systems. The objective of this work is to study the concepts and tools of complex networks to generate visualizations and analyses of co-authorship and citation networks of scientific articles on coronavirus.