Journal of the Korean Society for information Management (정보관리학회지)

Korean Society for Information Management (한국정보관리학회)
권호 표지
DOI QR코드

DOI QR Code

The Distinct Impact Dimensions of the Prestige Indices in Author Citation Networks

저자 인용 네트워크에서 명망성 지표의 차별된 영향력 측정기준에 관한 연구

  • 안혜림 (연세대학교 대학원 문헌정보학, 한국연구재단) ;
  • 박지홍 (연세대학교 문헌정보학과)
  • Received : 2016.05.18
  • Accepted : 2016.06.06
  • Published : 2016.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This study aims at proposing three prestige indices-closeness prestige, input domain, and proximity prestige- as useful measures for the impact of a particular node in citation networks. It compares these prestige indices with other impact indices as it is still unknown what dimensions of impact these indices actually measure. The prestige indices enable us to distinguish the most prominent actors in a directed network, similar to the centrality indices in undirected networks. Correlation analysis and principal component analysis were conducted on the author citation network to identify the differentiated implications of the three prestige indices from the existing impact indices. We selected simple citation counting, h-index, PageRank, and the three kinds of centrality indices which assume undirected networks as the existing impact measures for comparison with the three prestige indices. The results indicate that these prestige indices demonstrate distinct impact dimension from the other impact indices. The prestige indices reflect indirect impact while the others direct impact.

본 연구는 명망성 지표(closeness prestige, input domain, proximity prestige)를 인용 네트워크 내에서 특정 노드의 영향력 측정을 위한 유용한 척도로 제안하는 것을 목적으로 한다. 명망성 지표의 영향력 측정기준에 대해 알려진 바가 없으므로 본 연구는 이 세 개의 명망성 지표와 다른 영향력 지표를 비교하고자 한다. 무방향 네트워크의 중심성 지표와 유사하게 명망성 지표는 유방향 네트워크에서 특정 중심 노드들을 차별화 시켜준다. 저자 인용 네트워크에서 수행된 상관분석과 주성분분석을 통하여 본 연구는 기존 영향력 지표와 차별된 명망성 지표만의 측정기준을 발굴하였다. 세 개의 무방향 네트워크 중심성 지표와 더불어 단순인용수, h-index, PageRank를 본 연구에서 제시한 명망성 지표와 비교하였다. 이러한 명망성 지표는 기존 영향력 지표와는 차별화된 영향력을 측정하고 있다는 결과를 도출하였으며 명망성 지표는 간접적인 영향력을 기존의 다른 영향력 지표는 직접적인 영향력을 반영한다.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. Bollen, J., Rodriguez, M. A., & Van de Sompel, H. (2006). Journal status. Scientometrics, 69(3), 669-687. https://doi.org/10.1007/s11192-006-0176-z
  2. De Nooy, W., Mrvar, A., & Batagelj, V. (2011). Exploratory social network analysis with Pajek (27 vols.). New York: Cambridge University Press. http://dx.doi.org/10.1017/cbo9780511996368
  3. Ding, Y. (2011). Applying Weighted PageRank to Author Citation Networks. Journal of the American Society for Information Science and Technology, 62(2), 236-245. http://dx.doi.org/10.1002/asi.21452
  4. Ding, Y., & Cronin, B. (2011). Popular and/or prestigious? Measures of scholarly esteem. Information Processing & Management, 47(1), 80-96. http://dx.doi.org/10.1016/j.ipm.2010.01.002
  5. Erman, N. (2009). Citation analysis for e-government research. Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government, 244-253.
  6. Fortunato, S., Boguna, M., Flammini, A., & Menczer, F. (2008). Approximating PageRank from in-degree. Lecture Notes in Computer Science, 4936, 59-71. http://dx.doi.org/10.1007/978-3-540-78808-9_6
  7. Gonzalez-Pereira, B., Guerrero-Bote, V.P., & Moya-Anegon, F. (2010). A new approach to the metric of journals' scientific prestige: The SJR indicator. Journal of Informetrics, 4(3), 379-391. http://dx.doi.org/10.1016/j.joi.2010.03.002
  8. Knoke, D., & Burt, R. S. (1983). Prominence. In R. S. Burt & M. J. Minor (Eds.), Applied network analysis: A methodological introduction (pp. 195-222). Newbury Park, CA: Sage.
  9. Lee, Jae Yun (2006). Centrality measures for bibliometric network analysis. Journal of the Korean Society for Library and Information Science, 40(3), 191-214. http://dx.doi.org/10.4275/kslis.2006.40.3.191
  10. Leydesdorff, L. (1998). Theories of citation? Scientometrics, 43(1), 5-25. http://dx.doi.org/10.2139/ssrn.2279062
  11. Litvak, N., Scheinhardt, W. R. W., & Volkovich, Y. V. (2006). Probabilistic relation between In-Degree and PageRank. Proceedings of 4th International Workshop, Banff, Canada.
  12. Mrvar, A., & Batagelj, V. (2014). Pajek and Pajek-XXL: Programs for analysis and visualization of very large networks reference manual list of commands with short explanation version 4.0. Retrieved from http://pajek-and-pajekxxl.software.informer.com
  13. Musial, K., Kazienko, P., & Brodka, P. (2009). User position measures in social networks. Proceedings of the 3rd Workshop on Social Network Mining and Analysis, 6. http://dx.doi.org/10.1145/1731011.1731017
  14. Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12(5), 297-312. http://dx.doi.org/10.1016/0306-4573(76)90048-0
  15. Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B (EPJ B), 4(2), 131-134. http://dx.doi.org/10.1007/s100510050359
  16. Romero, D. M., & Kleinberg, J. M. (2010). The directed closure process in hybrid social-information networks, with an analysis of link formation on Twitter. Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, 138-145.
  17. Sohn, Dong-Won (2002). Social Network Analysis. Seoul: Kyoungmoon.
  18. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York: Cambridge University Press.
  19. Yan, E. J., & Ding, Y. (2009). Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the American Society for Information Science and Technology, 60(10), 2107-2118. http://dx.doi.org/10.1002/asi.21128
  20. Yan, E. J., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science and Technology, 63(7), 1313-1326. http://dx.doi.org/10.1002/asi.22680
  21. Yan, E. J., Ding, Y., & Sugimoto, C. R. (2011). P-Rank: An indicator measuring prestige in heterogeneous scholarly networks. Journal of the American Society for Information Science and Technology, 62(3), 467-477. http://dx.doi.org/10.1002/asi.21461