Bibliometric Analysis of the100 Highly-cited Articles about COVID-19.
Year: 2020
Type: article
Abstract: We have to indicate that the number of 100 was arbitrary. Collecting a large number of citations dose not necessary indicates that the study is the best and has a high level of evidence. This study by no means negate high quality important articles that have been published recently and had not enough time to increase their citations yet. Findings on COVID-19 Characteristics are rapidly changing and subject to selection bias. The current study was a cross-sectional study on August 6, 2020; therefore, our findings will be changed overtime.
Source: PubMed Central
Authors: Ahmadreza Afshar, Ali Tabrizi
Institutions: Urmia University, Urmia University of Medical Sciences
Language: English
Subfield: Library and Information Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3107281174