@Article{info:doi/10.2196/11567，作者=“Kan, Wei-Chih and Chou, Willy and Chien, Tsair-Wei and Yeh, Yu-Tsen and Chou, Po-Hsin”，标题=“使用作者加权方案发表在JMIR mHealth and uHealth论文的被引次数最多的作者:文献计量学分析”，期刊=“JMIR mHealth uHealth”，年=“2020”，月=“May”，日=“7”，卷=“8”，数=“5”，页=“e11567”，关键词=“between - centrality”;作者协作;谷歌地图;社会网络分析;知识概念图;背景:许多先前的论文都调查了学术界被引用次数最多的文章或最多产的作者，但很少有研究被引用次数最多的作者。这样做面临两个挑战，一个是一些不同的作者在文献计量数据中会有相同的名字，另一个是文章署名中共同作者的贡献不同。没有研究处理文献计量数据中重复名称的问题。虽然中间中心性(BC)是社会网络分析(SNA)中最流行的密度度之一，但很少有人应用BC算法来解释网络的特征。必须使用定量方案来计算加权作者学分，然后将这些指标应用于比较。 Objective: This study aimed to apply the BC algorithm to examine possible identical names in a network and report the most-cited authors for a journal related to international mobile health (mHealth) research. Methods: We obtained 676 abstracts from Medline based on the keywords ``JMIR mHealth and uHealth'' (Journal) on June 30, 2018. The author names, countries/areas, and author-defined keywords were recorded. The BCs were then calculated for the following: (1) the most-cited authors displayed on Google Maps; (2) the geographical distribution of countries/areas for the first author; and (3) the keywords dispersed by BC and related to article topics in comparison on citation indices. Pajek software was used to yield the BC for each entity (or node). Bibliometric indices, including h-, g-, and x-indexes, the mean of core articles on g(Ag)=sum (citations on g-core/publications on g-core), and author impact factor (AIF), were applied. Results: We found that the most-cited author was Sherif M Badawy (from the United States), who had published six articles on JMIR mHealth and uHealth with high bibliometric indices (h=3; AIF=8.47; x=4.68; Ag=5.26). We also found that the two countries with the highest BC were the United States and the United Kingdom and that the two keyword clusters of mHealth and telemedicine earned the highest indices in comparison to other counterparts. All visual representations were successfully displayed on Google Maps. Conclusions: The most cited authors were selected using the authorship-weighted scheme (AWS), and the keywords of mHealth and telemedicine were more highly cited than other counterparts. The results on Google Maps are novel and unique as knowledge concept maps for understanding the feature of a journal. The research approaches used in this study (ie, BC and AWS) can be applied to other bibliometric analyses in the future. ", issn="2291-5222", doi="10.2196/11567", url="https://mhealth.www.mybigtv.com/2020/5/e11567", url="https://doi.org/10.2196/11567", url="http://www.ncbi.nlm.nih.gov/pubmed/32379053" }