• Yung-Ze Cheng, Tsair-Wei Chien, Sam Yu-Chieh Ho, and Willy Chou.
• Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
• Medicine (Baltimore). 2023 Jul 14; 102 (28): e34301e34301.

BackgroundA new approach to showcasing author publications on a website involves using a visual representation instead of the conventional paper list. The creation of an impact beam plot (IBP) as a research profile for individuals is crucial, especially when incorporating collection edges that include self-cited articles through a rare cluster analysis technique not commonly found in the literature. This study presents the application of a unique method called the following-leading clustering algorithm (FLCA) to generate IBPs for 3 highly productive authors.MethodsFor the 3 highly productive authors, Sung-Ho Jang from South Korea, Chia-Hung Kao from Taiwan, and Chin-Hsiao Tseng from Taiwan, all their published articles indexed in the Web of Science Core Collection were downloaded. Sung-Ho Jang published 593 articles, Chia-Hung Kao published 732 articles, and Chin-Hsiao Tseng published 160 articles. To analyze and showcase their publications, the FLCA was utilized. This algorithm helped cluster their articles and identify representative publications for each author. To assess the effectiveness and validity of the FLCA algorithm, both network charts and heatmaps with dendrograms were employed. IBPs were then created and compared for each of the 3 authors, taking into consideration their h-index, x-index, and self-citation rate. This allowed for a comprehensive visual representation of their research impact and citation patterns.ResultsThe results show that these authors' h-index, x-index, and self-citation rates were (37, 44.01, 1.66%), (42, 61.47, 0.23%), and (37, 40.3, 6.62%), respectively. A higher value in these metrics indicates a more remarkable research achievement. A higher self-citation rate with a lower cluster number indicates that manuscripts are more likely to have been self-drafted. Using the FLCA algorithm, IBPs were successfully generated for each author.ConclusionThe FLCA algorithm allows for the easy generation of visual IBPs based on authors' publication profiles. These IBPs incorporate 3 important bibliometric metrics: h-index, x-index, and self-citations. These metrics are highly recommended for use by researchers globally, particularly with the self-citation rate, as they offer valuable insights into the scholarly impact and citation patterns of individual researchers.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.

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