Evaluation of top 100 high-attention articles related to the application of artificial intelligence in health knowledge management: an altmetric study

Purpose The purpose of this study is to examine the altmetrics of the top 100 high-attention articles related to the application of artificial intelligence (AI) in health knowledge management (HKM), with the aim of understanding their social media engagement and impact. Design/methodology/approach This study was conducted using an altmetric analysis method. The authors systematically retrieved all articles related to the application of AI in HKM indexed in the SCI-Expanded of the Web of Science database between 1992 and 2023. Using Altmetric Explorer, the authors identified the top 100 articles with the highest Altmetric Attention Scores (AASs) and analyzed their characteristics and altmetric indicators. The top 100 articles with the highest AASs were selected as the analytical sample. Findings Most articles were published in 2023. The median altmetric score and number of citations were 13 and 18, respectively. X (formerly Twitter) was the most widely used social media platform, accounting for 90.10% of all mentions. A positive correlation was observed between AASs and the number of citations (R2 = 0. 997). A majority of article readers were PhD students, predominantly from the fields of Computer Science, Medicine and Engineering, highlighting the interdisciplinary nature of the research. Originality/value To the best of the authors’ knowledge, this study is the first to provide a comprehensive altmetric analysis of high-attention articles on AI in HKM, revealing a strong empirical link between social media engagement and citation impact in this emerging field. The findings also uniquely identify the key professional groups and academic levels driving knowledge dissemination, offering valuable insights for researchers and publishers on how to increase the visibility and reach of scholarly work in this rapidly evolving domain.