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Aim: At the context of the chest and infectious diseases, the main goal of this study is to make a bibliometric analysis of publications on coronavirus disease 2019 (COVID-19). Visualizing it with visible and scientific mapping techniques is the secondary goal. Material and Methods: Raw data for 2020 have been downloaded from the Web of Science Core Collection database. A total of 787 articles were reviewed. Raw data were analyzed with Bibliometrix and VOSviewer. The articles about COVID-19, related with the respiratory system and infectious diseases were included. The perspectives of other disciplines were excluded with the analysis. Results: A total of 787 articles were published in 108 different journals. The average number of citations per article is 10.17. There are four studies with over 300 citations. The top three authors with the highest H index are Raoult D, Colson P and Rolasin JM. The h, g and m indices of the authors were calculated and the core authors were determined according to Lotka's law. The top three countries that publish the most articles are China, America and Italy. Finally, according to the word mining analysis, it was determined that the studies can be classified under three clusters. Conclusion: One of the tools that will accelerate the basic reading process in the face of the numerical increase rate of publications on COVID-19 is the bibliometric analysis results. The most up-to-date and basic information on treatment options can be found collectively in bibliometric studies.
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Stored only when both papers are in the corpus — 23 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.