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http://dx.doi.org/10.7465/jkdi.2015.26.2.335

The comparison of coauthor networks of two statistical journals of the Korean Statistical Society using social network analysis  

Chun, Heuiju (Department of Statistics & Information, Dongduk Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.2, 2015 , pp. 335-346 More about this Journal
Abstract
The purpose of this study is to compare not only network influence of individual coauthor but also the types and properties of two coauthor networks of Communications for Statistical Applications and Methods and the Korean Journal of Applied Statistics which are published by the Korean Statistical Society using social network analysis.As the result of two network structure comparison, density, inclusiveness, reciprocity and clustering coefficient which represent the type of coauthor networks show almost similar values and the Korean Journal of Applied Statistics has bigger values in average degree, average distance and diameter because it has more nodes than Communications for Statistical Applications and Methods. Finally two journals have very similar type of coauthor network. In the comparison of network centrality of two coauthor networks, closeness centrality and betweenness centrality of the Korean Journal of Applied Statistics are bigger than those of Communications for Statistical Applications and Methods at the statistical significance level 0.05. The coauthor network of the Korean Journal of Applied Statistics has faster information delivery and stronger betweenness than that of Communications for Statistical Applications.
Keywords
Coauthor; coauthor network; social network; social network analysis;
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Times Cited By KSCI : 7  (Citation Analysis)
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1 Barabasi, A. L., Jeong, H., Neda Z., Ravasz, E., Schubert, A. and Viesek, T. (2002). Evolution of the social network of scientific collaborations. PHYSICA, A311, 590-614.
2 Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92, 1170-82.   DOI   ScienceOn
3 Borner, K., Dall'Asta, L., Ke, W. and Vespignani, A. (2005). Studying the emerging global brain: Analyzing and visualizing the impact of co-authorship teams. Complexity, 10, 57-67.   DOI   ScienceOn
4 Choi, Y. and Lee, K. (2009). Analysis of types of journal paper coauthor: focused on Korean Public Administration Review (1989-2008). Korean Public Administration Review, 43, 51-72.
5 Choi, S., Kang C., Choi, H. and Kang, B. (2011). Social network analysis for a soccer game. Journal of the Korean Data & Information Science Society, 22, 1053-1063.
6 Cho, J. S. (2012). Inflow and outflow analysis of double majors using social network analysis. Journal of the Korean Data & Information Science Society, 23, 693-701.   DOI   ScienceOn
7 Chun, H. (2011). Analysis and application to customers' social roles using voice network of A telecom, company. The Korean Journal of Applied Statistics, 24, 1237-1248.   DOI   ScienceOn
8 Chun, H. and Leem, B. (2014). Face/non-face channel fit comparison of life insurance company and non-life insurance company using social network analysis. Journal of the Korean Data & Information Science Society, 25, 1207-1219.   DOI   ScienceOn
9 Coleman, J. (1988). Social capital in the creation of human capital. The American Journal of Sociology, 94, S95-S120.   DOI   ScienceOn
10 Fafchamps, M., Van der Leij, M. and Goyal, S. (2006). Scientific networks and co-authorship. University of Oxford Department of Economics Discussion Paper Series, 256.
11 Huang, M., Ahn, J. and Jahng, J. (2008). Patterns of Collaboration Networks : Co-authorship Analysis of MIS Quarterly from 1996 to 2004. Journal of Society for e-Business Studies, 13, 193-207.
12 Kretschmer, H. (1994). Coauthorship networks of invisible colleges and institutionalized communities. Scientometrics, 30, 363-369.   DOI
13 Li-chun, Y., Kretschmer, H., Hanneman, R. and Ze-yuan, L. (2006). Connection and stratification in research collaboration: An analysis of the COLLNET network. Information Processing and Management, 42, 1599-1613.   DOI   ScienceOn
14 Lee, M., Park, M., Lee, H. and Jin, S. (2011). Analysis of Papers in the Korean Journal of Applied Statistics by Co-Author Networks Analysis. The Korean Journal of Applied Statistics, 24, 1259-1270.   DOI   ScienceOn
15 Lee, S. (2010), A Preliminary Study on the Co-author Network Analysis of Korean Library & Information Science Research Community. Journal of Korean Library and Information Science Society, 41, 297-315.   DOI
16 Liu, X., Bollen, J., Nelson, M. L. and Sompel, H. V. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, 41, 1462-4180.   DOI   ScienceOn
17 Menezes, G. V., Ziviani, N., Laender, A. H. F. and Almeida, V. (2009). A geographic analysis of knowledge production in computer science. Paper presented at the International World Wide Web Conference Committee, Madrid, Spain.
18 Nam, S. H. and Seol, S. (2007), Coauthorship analysis of innovation studies in Korea : A social network perspective. Journal of Korea technology innovation society, 10, 605-628.
19 Nascimento, M. A., Sander, J. and Pound, J. (2003). Analysis of SIGMOD's co-authorship graph. SIGMOD Record, 32, 8-10.   DOI   ScienceOn
20 Newman, M. (2001a). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64, Art. No. 016131.
21 Newman, M. (2001b). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64, Art. No. 016132.
22 Rodriguez, M. A. and Pepe, A. (2008). On the relationship between the structural and socioacademic communities of co-authorship network. Journal of Infometrics, 2, 195-201.   DOI   ScienceOn
23 Newman, M. (2001c). The structure of scientific collaboration networks. Proceedings of the National Academy of Science, 98, 404-409.   DOI
24 Newman, M. (2003). Ego-centered networks and the ripple effect. Social Networks, 25, 83-95.   DOI   ScienceOn
25 Otte, E. and Rousseau, R. (2002). Social network analysis: a powerful strategy also for the information sciences. Journal of Information Science, 28, 444-453.
26 Velden, T., Haque, A. and Lagoze, C. (2010). A New Approach to Analyzing Patterns of Collaborationin Co-authorship Networks - Mesoscopic Analysis and Interpretation. arXiv:0911.4761.
27 Watts, D. J. and Strogatz, S. H. (1998). Collectively dynamics of small-world networks. Nature, 393, 440-442.   DOI   ScienceOn
28 Yan, E. and Ding, Y. (2009). Applying centrality measures to impact analysis: a co-authorship network analysi. Journal of the American Society for Information Science and Technology, 60, 2107-2118.   DOI   ScienceOn