Tornberg Haley, Moezinia Carine, Wei Chapman, Bernstein Simone A, Wei Chaplin, Al-Beyati Refka, Quan Theodore, Diemert David J
Cooper Medical School of Rowan University, Camden, NJ, United States.
Department of Medicine, Hospital for Special Surgery, New York, NY, United States.
JMIR Form Res. 2023 Jul 12;7:e41388. doi: 10.2196/41388.
The use of social media assists in the distribution of information about COVID-19 to the general public and health professionals. Alternative-level metrics (ie, Altmetrics) is an alternative method to traditional bibliometrics that assess the extent of dissemination of a scientific article on social media platforms.
Our study objective was to characterize and compare traditional bibliometrics (citation count) with newer metrics (Altmetric Attention Score [AAS]) of the top 100 Altmetric-scored articles on COVID-19.
The top 100 articles with the highest AAS were identified using the Altmetric explorer in May 2020. AAS, journal name, and mentions from various social media platforms (Twitter, Facebook, Wikipedia, Reddit, Mendeley, and Dimension) were collected for each article. Citation counts were collected from the Scopus database.
The median AAS and citation count were 4922.50 and 24.00, respectively. TheNew England Journal of Medicine published the most articles (18/100, 18%). Twitter was the most frequently used social media platform with 985,429 of 1,022,975 (96.3%) mentions. Positive correlations were observed between AAS and citation count (r=0.0973; P=.002).
Our research characterized the top 100 COVID-19-related articles by AAS in the Altmetric database. Altmetrics could complement traditional citation count when assessing the dissemination of an article regarding COVID-19.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/21408.
社交媒体的使用有助于向公众和卫生专业人员传播有关2019冠状病毒病(COVID-19)的信息。替代计量指标(即Altmetrics)是一种不同于传统文献计量学的方法,用于评估科学文章在社交媒体平台上的传播程度。
我们的研究目的是对关于COVID-19的Altmetric评分最高的前100篇文章的传统文献计量学指标(引用次数)与新指标(Altmetric关注度得分[AAS])进行特征描述和比较。
2020年5月使用Altmetric浏览器确定AAS最高的前100篇文章。收集每篇文章的AAS、期刊名称以及来自各种社交媒体平台(推特、脸书、维基百科、红迪网、Mendeley和Dimension)的提及次数。从Scopus数据库收集引用次数。
AAS中位数和引用次数中位数分别为4922.50和24.00。《新英格兰医学杂志》发表的文章最多(18/100,18%)。推特是最常使用的社交媒体平台,在1,022,975次提及中有985,429次(96.3%)。观察到AAS与引用次数之间存在正相关(r = 0.0973;P = 0.002)。
我们的研究通过Altmetric数据库中的AAS对前100篇与COVID-19相关的文章进行了特征描述。在评估关于COVID-19的文章传播情况时,Altmetrics可以补充传统的引用次数。
国际注册报告识别号(IRRID):RR2-10.2196/21408。