Okhovati Maryam, Arshadi Homa
Medical Library and Information Sciences Department, School of Management and Information Science, Kerman University of Medical Sciences, Kerman, Iran.
Med J Islam Repub Iran. 2021 Feb 9;35:20. doi: 10.47176/mjiri.35.20. eCollection 2021.
Coronavirus primarily targets the human respiratory system, COVID-19 (Coronavirus disease 2019) triggered in China in the late 2019. In March 2020, WHO announced the COVID-19 pandemic. This study aims to analyze and visualize the scientific structure of the COVID-19 publications using co-citation and co-authorship. This is a scientometric study. Web of Science Core Collection (WoSCC) was searched for all documents regarding COVID-19, MERS-Cov, and SARS-Cov from the beginning to 2020. An Excel spreadsheet was applied to gather and analyze the data and the CiteSpace was used to visualize and analyze the data. A total of 5159 records were retrieved in WoSCC. The structure of the network indicated that the network mean silhouette was low (0.1444), implying that the network clusters' identity is not identifiable with high confidence. The network modularity was 0.7309. The cluster analysis of the co-citation network on documents from 2003 to 2020 provided 188 clusters. The largest cluster entitled, "the Middle East respiratory syndrome coronavirus" had 255 nodes. The coauthorship network illustrated that the most prolific countries, USA, China, and Saudi Arabia, have focused on a specific field and have formed separate clusters. The present study identified the important topics of research in the field of COVID-19 based on co-citation networks as well as the analysis of clusters of countries' collaborations. Despite the similarities in the production behavior in prolific countries, their thematic focus varies so that a country like China plays a role in "Quantitative Detection" cluster, while USA is the leading country in the "Biological Evaluation" cluster.
冠状病毒主要侵袭人体呼吸系统，2019年末在中国引发了COVID-19（2019冠状病毒病）。2020年3月，世界卫生组织宣布COVID-19大流行。本研究旨在通过共被引和共同作者关系分析并可视化COVID-19相关出版物的科学结构。这是一项科学计量学研究。在科学网核心合集（WoSCC）中检索了从开始到2020年所有关于COVID-19、中东呼吸综合征冠状病毒（MERS-CoV）和严重急性呼吸综合征冠状病毒（SARS-CoV）的文献。使用Excel电子表格收集和分析数据，并使用CiteSpace对数据进行可视化和分析。在WoSCC中总共检索到5159条记录。网络结构表明网络平均轮廓系数较低（0.1444），这意味着网络集群的身份无法高度自信地识别。网络模块性为0.7309。对2003年至2020年文献的共被引网络进行聚类分析得到188个聚类。最大的聚类名为“中东呼吸综合征冠状病毒”，有255个节点。共同作者网络表明，发文量最多的国家，即美国、中国和沙特阿拉伯，专注于特定领域并形成了单独的聚类。本研究基于共被引网络以及国家合作聚类分析确定了COVID-19领域的重要研究主题。尽管发文量多的国家在产出行为上有相似之处，但其主题重点各不相同，例如中国在“定量检测”聚类中发挥作用，而美国是“生物学评估”聚类中的领先国家。
