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COVID-19 最受关注的 100 篇文章:基于文献计量分析的 Altmetric 研究。

Most notable 100 articles of COVID-19: an Altmetric study based on bibliometric analysis.

机构信息

Department of Internal Medicine, Biruni University Medical Faculty, Eski Londra Asfaltı, No. 10, Besyol, Kucukcekmece, Istanbul, Turkey.

Department of Anesthesiology and Reanimation, Biruni University Medical Faculty, Istanbul, Turkey.

出版信息

Ir J Med Sci. 2021 Nov;190(4):1335-1341. doi: 10.1007/s11845-020-02460-8. Epub 2021 Jan 18.

DOI:10.1007/s11845-020-02460-8
PMID:33459942
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7811952/
Abstract

OBJECTIVE

The purpose of this study is to guide researchers in the COVID-19 pandemic by evaluating the 100 most cited articles of COVID-19 in terms of bibliometric analysis, Altmetric scores, and dimension badges.

METHODS

"COVID-19" was entered as the search term in Thomson Reuter's Web of Science database. The 100 most cited articles (T100) were analyzed bibliometrically. Altmetric attention scores (AASs) and dimension badge scores of the articles were evaluated.

RESULTS

T100 articles were published from January to September 2020. The average citation of the top 100 articles on COVID-19 was 320 ± 344.3 (143-2676). The language of all articles was English. The average Altmetric value of T100 is 3246 ± 3795 (85-16,548) and the mean dimension badge value was 670 ± 541.6 (176-4232). Epidemiological features (n = 22) and treatment (n = 21) were at the top of the main topics of T100 articles.

CONCLUSION

The more citations an article is made, the more it indicates the contribution of that article to science. However, the number of citations is not always the only indicator of article quality. The existence of methods that measure the impact of the article outside the academia to measure the value of the article arises more in an issue that affects the whole world, such as the COVID-19 pandemic.

摘要

目的

本研究旨在通过对 COVID-19 100 篇被引频次最高的文章进行文献计量学分析、Altmetric 分数和维度徽章评分,为 COVID-19 研究人员提供指导。

方法

在 Thomson Reuter 的 Web of Science 数据库中输入“COVID-19”作为检索词。对 100 篇被引频次最高的文章(T100)进行文献计量学分析。评估文章的 Altmetric 关注度分数(AAS)和维度徽章分数。

结果

T100 文章发表于 2020 年 1 月至 9 月。COVID-19 前 100 篇文章的平均被引次数为 320±344.3(143-2676)。所有文章的语言均为英语。T100 的平均 Altmetric 值为 3246±3795(85-16548),平均维度徽章值为 670±541.6(176-4232)。T100 文章的主要主题中,排在前两位的是流行病学特征(n=22)和治疗(n=21)。

结论

文章被引频次越高,表明该文章对科学的贡献越大。然而,被引次数并不总是衡量文章质量的唯一指标。在影响全世界的问题(如 COVID-19 大流行)中,出现了更多衡量文章价值的方法,这些方法除了衡量文章在学术界之外的影响力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/f2804129b41d/11845_2020_2460_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/de4a86141376/11845_2020_2460_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/195a27dea236/11845_2020_2460_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/f2804129b41d/11845_2020_2460_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/de4a86141376/11845_2020_2460_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/195a27dea236/11845_2020_2460_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81e1/7811952/f2804129b41d/11845_2020_2460_Fig3_HTML.jpg

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