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Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19)
Background: The first outbreaks of the new coronavirus disease, named COVID-19, occurred at the end of December 2019. This disease spread quickly around the world, with the United States, Brazil and Mexico being the countries the most severely affected. This study aims to analyze the relationship be...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593954/ https://www.ncbi.nlm.nih.gov/pubmed/33096796 http://dx.doi.org/10.3390/ijerph17207690 |
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author | Martinez-Perez, Clara Alvarez-Peregrina, Cristina Villa-Collar, Cesar Sánchez-Tena, Miguel Ángel |
author_facet | Martinez-Perez, Clara Alvarez-Peregrina, Cristina Villa-Collar, Cesar Sánchez-Tena, Miguel Ángel |
author_sort | Martinez-Perez, Clara |
collection | PubMed |
description | Background: The first outbreaks of the new coronavirus disease, named COVID-19, occurred at the end of December 2019. This disease spread quickly around the world, with the United States, Brazil and Mexico being the countries the most severely affected. This study aims to analyze the relationship between different publications and their authors through citation networks, as well as to identify the research areas and determine which publication has been the most cited. Methods: The search for publications was carried out through the Web of Science database using terms such as “COVID-19” and “SARS-CoV-2” for the period between January and July 2020. The Citation Network Explorer software was used for publication analysis. Results: A total of 14,335 publications were found with 42,374 citations generated in the network, with June being the month with the largest number of publications. The most cited publication was “Clinical Characteristics of Coronavirus Disease 2019 in China” by Guan et al., published in April 2020. Nine groups comprising different research areas in this field, including clinical course, psychology, treatment and epidemiology, were found using the clustering functionality. Conclusions: The citation network offers an objective and comprehensive analysis of the main papers on COVID-19 and SARS-CoV-2. |
format | Online Article Text |
id | pubmed-7593954 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75939542020-10-30 Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) Martinez-Perez, Clara Alvarez-Peregrina, Cristina Villa-Collar, Cesar Sánchez-Tena, Miguel Ángel Int J Environ Res Public Health Article Background: The first outbreaks of the new coronavirus disease, named COVID-19, occurred at the end of December 2019. This disease spread quickly around the world, with the United States, Brazil and Mexico being the countries the most severely affected. This study aims to analyze the relationship between different publications and their authors through citation networks, as well as to identify the research areas and determine which publication has been the most cited. Methods: The search for publications was carried out through the Web of Science database using terms such as “COVID-19” and “SARS-CoV-2” for the period between January and July 2020. The Citation Network Explorer software was used for publication analysis. Results: A total of 14,335 publications were found with 42,374 citations generated in the network, with June being the month with the largest number of publications. The most cited publication was “Clinical Characteristics of Coronavirus Disease 2019 in China” by Guan et al., published in April 2020. Nine groups comprising different research areas in this field, including clinical course, psychology, treatment and epidemiology, were found using the clustering functionality. Conclusions: The citation network offers an objective and comprehensive analysis of the main papers on COVID-19 and SARS-CoV-2. MDPI 2020-10-21 2020-10 /pmc/articles/PMC7593954/ /pubmed/33096796 http://dx.doi.org/10.3390/ijerph17207690 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Martinez-Perez, Clara Alvarez-Peregrina, Cristina Villa-Collar, Cesar Sánchez-Tena, Miguel Ángel Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title | Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title_full | Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title_fullStr | Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title_full_unstemmed | Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title_short | Citation Network Analysis of the Novel Coronavirus Disease 2019 (COVID-19) |
title_sort | citation network analysis of the novel coronavirus disease 2019 (covid-19) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593954/ https://www.ncbi.nlm.nih.gov/pubmed/33096796 http://dx.doi.org/10.3390/ijerph17207690 |
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