Altmetric, Bibliometric, and Visualized Study of Top 100 Most Cited Papers in Digital Health

Abstract

Aim: This study aims to evaluate the research movements in the Digital Health topic through the most cited 100 products. Material and Method: Top-100 list was obtained by the help of Web of Science Core Collection (www.webofknowledge.com) database. Bibliometric analysis was employed to analyze the documents in detail in the area in question. Altmetric attention score provided by altmetric analysis was utilized to demonstrate the effect of articles on social media. Multiple linear regression analyses were applied to reveal related factors of Citation Count and Altmetric Attention Score. Results: The most-cited 100 papers in Digital Health topic were observed to be published between 2010 and 2020. Mean and standard deviation of the Citation Counts were 141.4±78. A poor positive association is noted between Citation Count and Altmetric Attention Score (r=0.256, p=0.012). Multiple linear regression analysis findings show that “Q2 level (p=0.050)”, “AAS” (p=0.002”), “Since 2013 Usage Count (p