Mehmet DOKUR, Mahmut DEMİRBİLEK, Mehmet KARADAĞ, Nüket GÜLER BAYSOY, Betül BORKU UYSAL

An altmetric study: Social attention based evaluation of top-100 publications about the COVID-19 pandemic from notification of the first case to the 6th month

Objective: Altmetrics, or alternative-metrics, have recently emerged as a web-based metrics measuring the impact of an individual article in social media accounts with an emphasis on the public attention/engagement with the research output. Aim of this study is to perform mid-2020 altmetric analysis of top-100 articles about COVID-19 that provoked the most online attention. Methods: Altmetric Explorer search was performed in June 3th ,2020. After ranked by altmetric attention score (AAS: an automatically calculated weighted count of all of the attention a research output has received in social media), articles that are not related by COVID-19 were excluded and the first-100 COVID-19-related articles were analyzed. Variables evaluated were (I) AAS, (II) dimensions-badge (interactive visualizations that showcase the citation data origins for individual publications), (III) month of publication, (IV) distribution of web-sources, (V) demographic-breakdown type distributions of citations, (VI) geographic-breakdown type distributions of citations, (VII) level-of-evidence (decided using SIGN-Criteria) (VIII) Q-categories ofscientific journals, and (IX) h-index. Descriptive and correlational statistics were performed. Kruskal-Wallis test was used for AAS and dimensions-badge value comparisons while post-hoc analyses were performed by Dunn test. Spearman correlation coefficients were calculated to detect linear relationship between numerical variables. Analyses were performed by SPSS- 23.0 and p

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