The Most-Cited Authors Who Published Papers in JMIR mHealth and uHealth Using the Authorship-Weighted Scheme: Bibliometric Analysis

doi:10.2196/11567

中山醫學大學機構典藏 CSMUIR > 中山醫學大學研究成果 > 期刊論文 > Item 310902500/24711

Please use this identifier to cite or link to this item: https://ir.csmu.edu.tw:8080/ir/handle/310902500/24711

Title:	The Most-Cited Authors Who Published Papers in JMIR mHealth and uHealth Using the Authorship-Weighted Scheme: Bibliometric Analysis
Authors:	Kan, WC;Chou, W;Chien, TW;Yeh, YT;Chou, PH
Keywords:	betweenness centrality;authorship collaboration;Google Maps;social network analysis;knowledge concept map;the author-weighted scheme
Date:	2020
Issue Date:	2022-08-09T08:06:47Z (UTC)
Publisher:	JMIR PUBLICATIONS, INC
ISSN:	2291-5222
Abstract:	Background: Many previous papers have investigated most-cited articles or most productive authors in academics, but few have studied most-cited authors. Two challenges are faced in doing so, one of which is that some different authors will have the same name in the bibliometric data, and the second is that coauthors' contributions are different in the article byline. No study has dealt with the matter of duplicate names in bibliometric data. Although betweenness centrality (BC) is one of the most popular degrees of density in social network analysis (SNA), few have applied the BC algorithm to interpret a network's characteristics. A quantitative scheme must be used for calculating weighted author credits and then applying the metrics in comparison. 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.
URI:	http://dx.doi.org/10.2196/11567 https://www.webofscience.com/wos/woscc/full-record/WOS:000530801900001 https://ir.csmu.edu.tw:8080/handle/310902500/24711
Relation:	JMIR MHEALTH AND UHEALTH ,2020 ,v8 ,issue 5
Appears in Collections:	[中山醫學大學研究成果] 期刊論文

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	203	View/Open

Loading...