https://socictopen.socict.org/files/original/e6a5cdae3308e2ce42c69cfae76fb47b.pdf eb9b41e970507d65ccd9f3d314e1e5d3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A bibliometric and co-occurrence analysis of COVID-19–related literature published between December 2019 and June 2020 Creator An entity primarily responsible for making the resource Md. Sayeed Al-Zaman Description An account of the resource Purpose The main purposes of this study were to analyze the document types and languages of published papers on coronavirus disease 2019 (COVID-19), along with the top authors, publications, countries, institutions, and disciplines, and to analyze the co-occurrence of keywords and bibliographic coupling of countries and sources of the most-cited COVID-19 literature. Methods This study analyzed 16,384 COVID-19 studies published between December 2019 and June 2020. The data were extracted from the Web of Science database using four keywords: “COVID-19,” “coronavirus,” “2019-nCoV,” and “SARS-CoV-2.” The top 500 mostcited documents were analyzed for bibliographic and citation network visualization. Results The studies were published in 19 different languages, and English (95.313%) was the most common. Of 157 research-producing countries, the United States (25.433%) was in the leading position. Wang Y (n=94) was the top author, and the BMJ (n=488) was the top source. The University of London (n=488) was the leading organization, and medicine-related papers (n=2,259) accounted for the highest proportion. The co-occurrence of keywords analysis identified “coronavirus,” “COVID-19,” “SARS-CoV-2,” “2019-nCoV,” and “pneumonia” as the most frequent words. The bibliographic coupling analysis of countries and sources showed the strongest collaborative links between China and the United States and between the New England Journal of Medicine and the JAMA. Conclusion Collaboration between the United States and China was key in COVID-19 research during this period. Although BMJ was the leading title for COVID-19 articles, the co-author link between New England Journal of Medicine and JAMA was the strongest. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, bibliometric analysis, publications Identifier An unambiguous reference to the resource within a given context 10.6087/kcse.230 Source A related resource from which the described resource is derived Science Editing Publisher An entity responsible for making the resource available Korean Council of Science Editors Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science (General)