Lim Sher-Wei, Chou Willy, Chow Julie Chi
Department of Neurosurgery, Chi-Mei Medical Center, Chiali, Tainan, Taiwan.
Department of Nursing, Min-Hwei College of Health Care Management, Tainan, Taiwan.
Medicine (Baltimore). 2025 Aug 29;104(35):e42657. doi: 10.1097/MD.0000000000042657.
The rise of bibliometrics is closely linked to visualization tools. However, visuals produced by these tools often lack clarity and offer limited valuable information. There is a need for a comprehensive method that concisely describes key article metadata and highlights unexpected aberrant data patterns (UADPs) on slope graphs instead of traditional burst bar charts in CiteSpace. This study examined metadata from 26,555 articles in the journal Heliyon'' sourced from the Web of Science Core Collection. It assessed metrics and impacts across 10 critical metadata aspects, using the Rasch model to identify UADP displayed on slope graphs. The performance analytics, summary reports, and visual validations model, with performance analytics, summary reports, and visual validations, was applied to display findings. The slope graph, offering more valuable information, was proposed to replace traditional burst bar charts in CiteSpace. The analysis focused on the top 10 elements from 10 different areas, providing a detailed understanding of the journal and its significant contributors in performance analytics. China emerged as the leading country in research contributions to "Heliyon" with a distinct UADP in summary reports. The visual validations showed that: the UADPs were highlighted in China and Covenant University (Nigeria) by the outfit mean square error (MNSQs = 5.28 and 2.22, respectively, >2.0), and the keyword PERFORMANCE'' has a lower outfit MNSQ (=1.95, with a data pattern similar to other top 9 keywords plus). The study emphasized slope graph with UADPs over traditional burst bar chart in bibliometrics. The study highlights China's dominance in research output for the journal "Heliyon," identified through advanced slope graphs showing a significantly higher outfit MNSQ (=5.28). Future bibliometric analyses should emphasize UADPs alongside top-ranked elements to provide deeper insights into article characteristics.
文献计量学的兴起与可视化工具密切相关。然而，这些工具生成的可视化内容往往缺乏清晰度，提供的有价值信息有限。需要一种全面的方法，能够简洁地描述关键文章元数据，并在斜率图上突出显示意外异常数据模式（UADPs），而不是CiteSpace中传统的爆发条形图。本研究检查了来自科学网核心合集的《Heliyon》杂志上26555篇文章的元数据。它评估了10个关键元数据方面的指标和影响，使用拉施模型识别斜率图上显示的UADP。应用性能分析、总结报告和视觉验证模型，包括性能分析、总结报告和视觉验证，来展示研究结果。有人提议用提供更多有价值信息的斜率图取代CiteSpace中的传统爆发条形图。分析聚焦于10个不同领域的前10个元素，以便在性能分析中详细了解该期刊及其重要贡献者。中国在对《Heliyon》的研究贡献方面成为领先国家，在总结报告中有明显的UADP。视觉验证表明：中国和科凡大学（尼日利亚）的UADP通过装备均方误差（MNSQs分别为5.28和2.22，>2.0）得到突出显示，关键词“PERFORMANCE”的装备MNSQ较低（=1.95，其数据模式与其他前9个关键词加类似）。该研究强调在文献计量学中，带有UADPs的斜率图优于传统爆发条形图。该研究突出了中国在《Heliyon》期刊研究产出方面的主导地位，这是通过显示明显更高装备MNSQ（=5.28）的先进斜率图确定的。未来的文献计量分析应在强调排名靠前的元素的同时突出UADPs，以便更深入地了解文章特征。
