Analysis of Scientific Collaboration Networks among Authors, Institutions, and Countries Studying Adolescent Myopia Prevention and Control: A Review Article.
Background
Studies related to the prevention and control of myopia in adolescents have increased rapidly, but only a few have measured the levels of scientific collaboration among authors, institutions and countries in this field. Thus, in this study, we aimed to reveal the status and levels of scientific collaboration in this field.


Methods
The research population included all published papers in the field of adolescent myopia prevention and control indexed in the Web of Science databases from 1997-2016. The co-authorship networks were drawn using SATI (Statistical Analysis Toolkit for Informetrics), Ucinet and VOS viewer (Visualisation of Similarities viewer). Active authors and some measures of co-author network, including degree centrality, closeness, betweenness, density and diameter, were also assessed.


Results
Overall, 610 records were obtained, and a number of publications developed through an increase in different collaboration types, with cooperation among authors and institutions as the most apparent ones. The top ten active authors and institutions were identified. The density of cooperative networks of the top 70 authors and the first 69 institutions were 0.043 and 0.011, respectively, with corresponding diameters of five and six, respectively. Seven distinct clusters formed the cooperation network among 38 countries. The top three clusters were centered in China, the United States and Australia, also identified as the most productive countries.


Conclusion
The flow of information is slow and the collaboration among authors and institutions in the network are not close enough. Thus, multiple collaboration types should be encouraged in this field, especially among countries.
['Wu|Wenwen|W|', 'Xie|Yaofei|Y|', 'Liu|Xiangxiang|X|', 'Gu|Yaohua|Y|', 'Zhang|Yuting|Y|', 'Tu|Xinlong|X|', 'Tan|Xiaodong|X|']
Collaboration Myopia Prevention and control Social network analysis