A bibliometric mapping of malaysian publication using co-word analysis

Bibliometric maps or science maps are figurative representation of scientific field or organization in which elements of the map are associated with topic or themes. In this study, the method that has been chosen to perform bibliometric mapping is co-words analysis. Main objective for this study is...

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Main Authors: Nadzar, N. M. A. M., Bakri, A., Ibrahim, R.
Format: Article
Language:English
Published: International Center for Scientific Research and Studies 2017
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Online Access:http://eprints.utm.my/id/eprint/76318/1/AryatiBakri_ABibliometricMappingofMalaysianPublication.pdf
http://eprints.utm.my/id/eprint/76318/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033710382&partnerID=40&md5=2ee2c1eb7be1a76496e518fd9a1005f1
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spelling my.utm.763182018-06-29T22:01:28Z http://eprints.utm.my/id/eprint/76318/ A bibliometric mapping of malaysian publication using co-word analysis Nadzar, N. M. A. M. Bakri, A. Ibrahim, R. QA75 Electronic computers. Computer science Bibliometric maps or science maps are figurative representation of scientific field or organization in which elements of the map are associated with topic or themes. In this study, the method that has been chosen to perform bibliometric mapping is co-words analysis. Main objective for this study is to identify the research progress that been achieved by previous researchers and future direction which has the potential to be discovered by younger researchers. Set of data been downloaded from Scopus database. In this study total of 2360 successfully downloaded which has been sorted the highest cited articles and all subject area is selected from year 1995 to 2015. By using Vosviewer, title and abstract from corpus is manipulated in order to produce cluster of co-words analysis. As for result, there are 5 cluster words being produce in the software. Three of clusters are related to medicine, pharmacy and clinical namely as cluster 1, cluster 4 and cluster 5. In cluster 2 is related to agricultural, environment and forestry whereas the last cluster, cluster 3 is more relate to children development, adult health and health in developing countries. Highest and low frequency word also reported in this study. Highest frequency can be considered as the most research area that become researcher's choice in this past 20 years. Whereas for low frequency words is the potential words that can be a guidance for young researchers to choose which research area or domain that they can gain the interest and do the next exploration. International Center for Scientific Research and Studies 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/76318/1/AryatiBakri_ABibliometricMappingofMalaysianPublication.pdf Nadzar, N. M. A. M. and Bakri, A. and Ibrahim, R. (2017) A bibliometric mapping of malaysian publication using co-word analysis. International Journal of Advances in Soft Computing and its Applications, 9 (3). pp. 90-113. ISSN 2074-8523 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033710382&partnerID=40&md5=2ee2c1eb7be1a76496e518fd9a1005f1
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Nadzar, N. M. A. M.
Bakri, A.
Ibrahim, R.
A bibliometric mapping of malaysian publication using co-word analysis
description Bibliometric maps or science maps are figurative representation of scientific field or organization in which elements of the map are associated with topic or themes. In this study, the method that has been chosen to perform bibliometric mapping is co-words analysis. Main objective for this study is to identify the research progress that been achieved by previous researchers and future direction which has the potential to be discovered by younger researchers. Set of data been downloaded from Scopus database. In this study total of 2360 successfully downloaded which has been sorted the highest cited articles and all subject area is selected from year 1995 to 2015. By using Vosviewer, title and abstract from corpus is manipulated in order to produce cluster of co-words analysis. As for result, there are 5 cluster words being produce in the software. Three of clusters are related to medicine, pharmacy and clinical namely as cluster 1, cluster 4 and cluster 5. In cluster 2 is related to agricultural, environment and forestry whereas the last cluster, cluster 3 is more relate to children development, adult health and health in developing countries. Highest and low frequency word also reported in this study. Highest frequency can be considered as the most research area that become researcher's choice in this past 20 years. Whereas for low frequency words is the potential words that can be a guidance for young researchers to choose which research area or domain that they can gain the interest and do the next exploration.
format Article
author Nadzar, N. M. A. M.
Bakri, A.
Ibrahim, R.
author_facet Nadzar, N. M. A. M.
Bakri, A.
Ibrahim, R.
author_sort Nadzar, N. M. A. M.
title A bibliometric mapping of malaysian publication using co-word analysis
title_short A bibliometric mapping of malaysian publication using co-word analysis
title_full A bibliometric mapping of malaysian publication using co-word analysis
title_fullStr A bibliometric mapping of malaysian publication using co-word analysis
title_full_unstemmed A bibliometric mapping of malaysian publication using co-word analysis
title_sort bibliometric mapping of malaysian publication using co-word analysis
publisher International Center for Scientific Research and Studies
publishDate 2017
url http://eprints.utm.my/id/eprint/76318/1/AryatiBakri_ABibliometricMappingofMalaysianPublication.pdf
http://eprints.utm.my/id/eprint/76318/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033710382&partnerID=40&md5=2ee2c1eb7be1a76496e518fd9a1005f1
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score 13.211869