Ranking of Latin-American scientific communities and their response to the emergency of COVID-19
Authors
Daniela Aguirre Guerrero, Juan Carlos López García, Karen Samara Miranda Campos
Abstract
The social network analysis has been successfully used to learn the nature and relationship of knowledge construction and scientific collaborations. In particular, the analysis of co-authorship and citation networks allows to study the arise and impact of new research trends and research groups by using algorithms for community detection and node ranking. Most of the studies in this direction focus on identifying the centrality and influence of individual scientists; however, a research group should hold a more influential position, and thus plays a more important role. Moreover, the identification and ranking of research groups is a significant component to understand how the scientific collaborations should be molded by disruptive events, such as the Coronavirus Disease 2019 (COVID-19).
The COVID-19 brought numerous challenges to the global scientific community, which has impacted the scientific collaboration dynamics in different knowledge areas from social to basic sciences. The COVID-19 research landscape has been presented in studies focused on the top productive regions, i.e., North America, Europe, and China. However, the scientific community of developing regions, such as Latin-America, have their own collaboration dynamics and research interests. This study aimed to investigate the collaboration relationships and research topics of the Latin-American scientific community on COVID-19, to identify and rank research groups of different knowledge areas.
The presented analysis was developed on the studies published in 2019 by authors affiliated with Latin-American institutions. First, the articles were retrieved from the Scopus database, then an analysis of co-authorship and citation networks over time and space was performed to identify the most productive countries, authors, and their collaboration dynamics and research interests. Finally, an algorithm for community ranking is proposed and applied to identify the most influential research groups on different knowledge areas. The main contributions of this study are a novel algorithm for community ranking and the COVID-19 research landscape of the Latin-American scientific community.
Keywords
Community ranking, scientific networks, COVID-19