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Ying Yang
Ying Yang
Library of China Medical University, North 2nd Road 92, Heping Ward, Shenyang 110001, China yywin5006@126.com
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Mingzhi Wu
Mingzhi Wu
Library of Shenyang Pharmaceutical University, Shenyang, People's Republic of China gongzi.new@163.com
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Lei Cui
Lei Cui
Department of Medical Informatics and Information System, China Medical University, Shenyang, People's Republic of China
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Abstract
Visualization of subject structure based on co-word analysis is used to explore the concept network and developmental tendency in certain field. There are many visualization methods for co-word analysis. However, integration of results by different methods is rarely reported. This article addresses the knowledge gap in this field of study. We compare three visualization methods: Cluster tree, strategy diagram and social network maps, and integrate different results together to one result through co-word analysis of medical informatics. The three visualization methods have their own character: cluster trees show the subject structure, strategic diagrams reveal the importance of topic themes in the structure, and social network maps interpret the internal relationship among themes. Integration of different visualization results to one more readable map complements each other. And it is helpful for researchers to get the concept network and developmental tendency in a certain field.
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| Scientometrics | |
|---|---|
| Language | English |
| Size | B5 |
| Year of Foundation |
1978 |
| Volumes per Year |
1 |
| Issues per Year |
12 |
| Founder | Akadémiai Kiadó |
| Founder's Address |
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. |
| Publisher | Akadémiai Kiadó Springer Nature Switzerland AG |
| Publisher's Address |
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. CH-6330 Cham, Switzerland Gewerbestrasse 11. |
| Responsible Publisher |
Chief Executive Officer, Akadémiai Kiadó |
| ISSN | 0138-9130 (Print) |
| ISSN | 1588-2861 (Online) |
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