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Lin, Gege
- Research Preferences of the G20 Countries:A Bibliometrics and Visualization Analysis
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Authors
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1 WISE Lab, Dalian University of Technology, Dalian, CN
1 WISE Lab, Dalian University of Technology, Dalian, CN
Source
Current Science, Vol 115, No 8 (2018), Pagination: 1477-1485Abstract
The purpose o f this study is to reveal the differences both in research output and research preferences o f the G20 countries. The research outputs o f the nineteen G20 countries (excluding the European Union) are measured based on their publications indexed in Web of Science. The research preferences o f the G20 countries were studied by comparing their research output in each research subject. Clustering method was then employed to classify the countries according to their research preferences. Nineteen countries are classified into four clusters. Countries assigned to the same cluster are similar in distribution of research subjects. In the end, by VOSviewer, we showed the research pattern o f each cluster. For example, USA in Cluster A is characterized by the emphasis on medical sciences and China in Cluster C is characterized by paying more attention to physical sciences.Keywords
Bibliometrics, Country-Level Studies, G20 Countries, Research Preferences, VOSviewer.Full Text
References
- Callaghan, M., Ghate, C., Pickford, S. and Rathinam, F., Global Cooperation Among G20 Countries: Responding to the Crisis and Restoring Growth. 2014, 1-21.
- Yang, L. Y., Yue, T., Ding, J. L. and Han, T., A comparison of disciplinary structure in science between the G7 and the BRIC countries by bibliometric methods. Scientometrics, 2012, 93, 497-516.
- Bouabid, H., Paul-Hus, A. and Lariviere, V., Scientific collaboration and high-technology exchanges among BRICS and G-7 countries. Scientometrics, 2016, 106, 873-899.
- Reuters, T., The research and innovation performance of the G20. Thompson Reuters, London, 2014.
- Hu, Z., Lin, G., Sun, T. and Wang, X., An EU without the UK: mapping the UK’s changing roles in the EU scientific research. Scientometrics, 2018, 115(3), 1185-1198.
- Hu, Z., Guo, F. and Hou, H., Mapping research spotlights for different regions in China. Scientometrics, 2017, 110, 779-790.
- Almeida, J. A. S., Pais, A. A. C. C. and Formosinho, S. J., Science indicators and science patterns in Europe. J. Informetr., 2009, 3, 134-142.
- Singhal, A., Modern information retrieval: A brief overview. IEEE Data Eng. Bull., 2001, 24, 35-43.
- Zhao, K. and Suzuki, E., Clustering classifiers learnt from local datasets based on cosine similarity. 2015, 150-159.
- Eck, N. J. V. and Waltman, L., VOSviewer Manual, version 1.6.8, CWTS, Leiden Google Scholar, 27 April 2018, 1-51.
- Ding, Y., Rousseau, R. and Wolfram, D., Measuring Scholarly Impact, Springer International, Pu, 2016.
- van Eck, N. and Waltman, L., Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 2009, 84, 523-538.
- European Commission Directorate-General for Telecommunications IMAE. The European Report on Science and Technology Indicators. 1994.
- Glanzel, W., Leta, J. and Thijs, B., Science in Brazil. Part 1: A macro-level comparative study. Scientometrics, 2006, 67, 67-86.
- Fu, H., Chuang, K., Wang, M. and Ho, Y., Characteristics of research in China assessed with essential science indicators. Scientometrics, 2011, 88, 841-862.