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The novel coronavirus disease 2019 (COVID-19) is a global pandemic. This study’s aim was to identify and characterize the top 100 COVID-19-related scientific publications, which had received the highest Altmetric Attention Scores (AASs). Hence, we searched Altmetric Explorer using search terms such as “COVID” or “COVID-19” or “Coronavirus” or “SARS-CoV-2” or “nCoV” and then selected the top 100 articles with the highest AASs. For each article identified, we extracted the following information: the overall AAS, publishing journal, journal impact factor (IF), date of publication, language, country of origin, document type, main topic, and accessibility. The top 100 articles most frequently were published in journals with high (>10.0) IF (n = 67), were published between March and July 2020 (n = 67), were written in English (n = 100), originated in the United States (n = 45), were original articles (n = 59), dealt with treatment and clinical manifestations (n = 33), and had open access (n = 98). Our study provides important information pertaining to the dissemination of scientific knowledge about COVID-19 in online media.
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Stored only when both papers are in the corpus — 7 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.