The normalization of co-authorship networks in the bibliometric evaluation: the government stimulation programs of China and Korea
- 772 Downloads
Using co-authored publications between China and Korea in Web of Science (WoS) during the one-year period of 2014, we evaluate the government stimulation program for collaboration between China and Korea. In particular, we apply dual approaches, full integer versus fractional counting, to collaborative publications in order to better examine both the patterns and contents of Sino-Korean collaboration networks in terms of individual countries and institutions. We first conduct a semi-automatic network analysis of Sino-Korean publications based on the full-integer counting method, and then compare our categorization with contextual rankings using the fractional technique; routines for fractional counting of WoS data are made available at http://www.leydesdorff.net/software/fraction. Increasing international collaboration leads paradoxically to lower numbers of publications and citations using fractional counting for performance measurement. However, integer counting is not an appropriate measure for the evaluation of the stimulation of collaborations. Both integer and fractional analytics can be used to identify important countries and institutions, but with other research questions.
KeywordsCo-authorship Collaboration Fractional counting Korea China Social network analysis Integer counting
- Anderson, J., Collins, P. M. D., Irvine, J., Isard, P. A., Martin, B. R., Narin, F., & Stevens, K. (1988a). On-line approaches to measuring national scientific output: A cautionary tale. Science and Public Policy, 15(3), 153–161.Google Scholar
- Anderson, J., Collins, P. M. D., Irvine, J., Isard, P. A., Martin, B. R., Narin, F., & Stevens, K. (1988b). On-line approaches to measuring national scientific output: A cautionary tale. Science and Public Policy, 15(3), 153–161.Google Scholar
- Galam, S. (2010). Integrating multiple coauthorship in the quantitative evaluation of individual’s scientific records. Arxiv preprint arXiv:1007.3708.
- Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. CA: University of California, Riverside. Retrieved July 1, 2013 from http://faculty.ucr.edu/~hanneman.
- Holmberg, K. (2015). Altmetrics for information professionals: Past, present, and future. Waltham, MA: Chandos Publishing.Google Scholar
- Korea Research Foundation. (2014). 2014 ECSAC-Korea Journal Editors Workshop. Daejeon: Korea Research Foundation.Google Scholar
- Kuhn, T. S. (1970). The structure of scientific revolutions. Chicago: Chicago University Press.Google Scholar
- Kwon, K. S., Park, H. W., So, M. H., & Leydesdorff, L. (2012). Has globalization strengthened South Korea’s national research system? National and international dynamics of the Triple Helix of scientific coauthorship relationships in South Korea. Scientometrics, 90(1), 163–176.CrossRefGoogle Scholar
- Lee, K. (2014). Schumpeterian analysis of economic catch-up. Cambridge: Cambridge University Press.Google Scholar
- Leydesdorff, L. (1988). Problems with the ‘measurement’ of national scientific performance. Science and Public Policy, 15(3), 149–152.Google Scholar
- Leydesdorff, L. (2015). The sciences are discursive constructs: The communication perspective as an empirical philosophy of science. In L. Cantoni & J. A. Danowski (Eds.), Communication and Technology (pp. 553–562). Berlin and Boston: De Gruyter Mouton.Google Scholar
- Leydesdorff, L., & Shin, J. C. (2011). How to evaluate universities in terms of their relative citation impacts: Fractional counting of citations and the normalization of differences among disciplines. Journal of the American Society for Information Science and Technology, 62(6), 1146–1155.CrossRefGoogle Scholar
- Mehmood, A., Choi, G. S., & von Feigenblatt, O. F., & Park, H. W. (2016 accepted). Proving ground for social network analysis in the emerging research area “Internet of Things” (IoT). Scientometrics. doi: 10.1007/s11192-016-1931-4.
- Morris, S. A. (2005). Unified Mathmatical Treatment of Complex Cascaded Bipartite Networks: The Case of Collections of Journal Papers. Oklahoma State University. Retrieved from http://digital.library.okstate.edu/etd/umi-okstate-1334.pdf. Unpublished Ph.D. Thesis.
- Narin, F. (1976). Evaluative bibliometrics: The use of publication and citation analysis in the evaluation of scientific activity. Washington, DC: National Science Foundation.Google Scholar
- Rana, S. (2012). Bibliometric analysis of output and visibility of science and technology in Singapore during 2000–2009. Webology, 9(1), Article 96. http://www.webology.org/2012/v9n1/a96.html.
- Tanksalvala, S. (20 October, 2014). Web of Science now includes expanded coverage of top Korean journals. Web of Sceicne. http://endnote.com/blog/web-science-now-includes-expanded-coverage-top-korean-journals.
- UNESCO. (2015). UNESCO Science report-towards 2030. Paris: UNESCO Publishing.Google Scholar
- van Liere, D. (2004). Interpretation of UCINET Output. Essex Summer School Version 1.0.Google Scholar
- Velez-Cuartas, G., Lucio-Arias, D., & Leydesdorff, L. (2016, forthcoming). Regional and global science: Latin American and Caribbean publications in the SciELO Citation Index and the Web of Science. El Profesional de la Información; preprint at arXiv:1510.02453.
- Yoon, J. W., & Park. H. W. (2016 Accepted). Triple helix dynamics of South Korea’s innovation system: A network analysis of inter-regional technological collaborations. Quality & Quantity. doi: 10.1007/s11135-016-0346-x.
- Yoon, J., Yang, J. S., & Park, H. W. (2015). Triple helix patterns and dynamics in Korea–China scientific collaborations. Daegu, Korea: Presented to the DISC.Google Scholar
- Zhou, P. & Leydesdorff, L. (2016). A comparative study of the citation impact of Chinese journals with priority funding. Presented to 1st international symposium on webometrics, informetrics & scientometrics (ISWIS) 17 October, 2015 Zhejiang University, Hangzhou, China. Frontiers in Research Metrics and Analytics.Google Scholar
- Zhou, Q., Leng, F., & Leydesdorff, L. (2015). The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS. Chinese Journal of Library and Information Science, 8(2), 11–24.Google Scholar