Assessing the Relationship Between Traditional Citation-based Metrics and New Metrics (Altmetrics / Dimensions / Number of Tweets) in COVID-19 & Eye Research

Abstract

Abstract Background: Traditional peer-reviewed publications are the most common forums for disseminating scientific information. With the rising popularity of social media, altmetric studies have gained importance in the assessment of impact values of scientific research. In the framework of COVID-19 and eye research, this study aimed to compare activity on new metrics with traditional bibliometric systems using highly cited publications. Methods: Using the term "COVID-19 & Eye," data from articles in last one year (March 2020 to April 2021) were collected from the Web of Science Core Collection (WoS) database. Author name, publication year, major topic, study type, journal name, journal impact factor, H-index, total citation number (TCN), Altmetric Attention Score (AAS), number of tweets (NT) and Dimensions score were studied in the top 100 cited articles list (T100 list). The bibliometric data was visualized using the VOSviewer software. For analysis, the Spearman correlation test and descriptive statistics were used. Results: In our WoS search, we found 720 articles with the term "COVID-19 & Eye". The mean TCN and AAS in T100 list were 22.51±62.41 and 299.11 ±2406.74, respectively. Total citation number showed moderate positive correlation with AAS and strong positive correlation with NT and Dimensions score (r=0.427, r=0.806, r=0.877, respectively, p=0.001 for all). Journal impact factor and H-index showed substantial significant positive correlations with AAS and NT. Conclusion: AAS, particularly Twitter and Dimensions score have a substantial positive correlation with traditional bibliometric data of COVID-19 and eye research.

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