Title:
Analysis of Co-authorship Network Structure in Traditional Medicine Studies in the Period 2008-2017
Fatemeh Makkizadeh Farzaneh Sa'adat Elaheh Ja'fari Manesh
Associated Professor of Information Science and Knowledge studies,Yazd University , Faculty of Social Sciences,Yazd M. A., Scientometrics, Department of Knowledge and Informayion Science, school of social Science, Yazd University, Yazd,Iran.. M. A., Scientometrics, Department of Knowledge and Informayion Science, school of social Science, Yazd University, Yazd,Iran..
Abstract:
Introduction: The purpose of this research is to draw up and analyze a collaborative network of researchers in the field of traditional medicine. Methodology: The present study is of applied type implemented with a scientometric approach. Articles related to the search were retrieved from the PubMed website by searching the phrase "traditional medicine" in the subject heading "mesh" in the field of traditional medicine during 2008-2017. For plotting and analyzing the co-authorship network of the articles, the UCnet software and its complementary package, namely NetDraw, were used while the Excel spreadsheet software was employed to provide a co-authorship matrix. Results: The review on the authors' performance showed that WANG, WANG, and LI obtained the highest ranks in production index with 120, 108, and 80 articles, respectively. The review of the author's co-authorship network also revealed that WANG (5.304) and WANG (3.335) enjoy a good position in the network in terms of betweenness index. According to the ranking index, WANG (12.332) and LI (9.838) are closest with other network nodes. The growth of scientific production in traditional medicine area in the years 2015 and 2011 was ascending while the trend was descending in the years 2016-2017. The highest number of scientific productions has been recorded in China and the United States. Conclusions: The articles in the studied area have been developed in collaboration between weak and strong authors. In other words, the strong authors with the highest abundance have collaborated with the weakest and least productive writers.
Keyword:
Traditional medicine, Social networks analysis, Co-authorship, Scientometrics, PubMed