https://doi.org/10.1140/epjb/s10051-024-00734-z
Regular Article - Statistical and Nonlinear Physics
Overview of the initial phase of scientific production on COVID-19 during the pandemic
1
Modelagem Computacional e Tecnologia Industrial, Centro Universitário SENAI CIMATEC, Av. Orlando Gomes, 1845, 41650-010, Salvador, BA, Brazil
2
Programa de Difusão do Conhecimento, Universidade do Estado da Bahia, R. Silveira Martins, 2555, 41150-000, Salvador, Bahia, Brazil
3
Programa de Difusão do Conhecimento, Instituto Federal da Bahia, R. Emídio dos Santos, s/n, 40301-015, Salvador, Bahia, Brazil
4
Departamento de Ciências Exatas e da Terra, Universidade do Estado da Bahia, R. Silveira Martins, 2555, 41150-000, Salvador, Bahia, Brazil
Received:
14
May
2024
Accepted:
17
June
2024
Published online:
8
July
2024
A novel virus begin to spread worldwide in 2020. Many studies have been conducted to better understand the outbreak that continues to affect the global population. The contribution of the present study is to provide an overview of the papers published in the first months since recognition of the first case of COVID-19. For this, a survey of scientific publications during the first 5 months of the outbreak was conducted. Semantic, coauthorship and citation networks were used to identify the most relevant themes and authors during the cited period. Coauthorship indicated that scientists from several countries had joined forces in the fight against the pandemic to produce many joint scientific publications on the newly discovered virus and the disease it caused. Coauthorship was spread across 1170 author groups. Regarding the semantic network of titles, we found that it was a hybrid network because it presented the small-world phenomenon and a power law in its degree distribution and was therefore scale invariant. Considering the citation network, we found that the distribution of indegrees followed a power law, and with it, we observed the most cited works due to their importance to the area and their cumulative advantage. The coauthorship, semantic, and citation networks clearly show some characteristics of complex systems.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
