정보관리학회지 (Journal of the Korean Society for information Management)

  • 제29권2호
  • /
  • Pages.193-204
  • /
  • 2012
  • /
  • 1013-0799(pISSN)
  • /
  • 2586-2073(eISSN)
한국정보관리학회 (Korean Society for Information Management)
권호 표지
DOI QR코드

DOI QR Code

문헌 단위 인용 네트워크 내 인용과 중심성 지수 간 관계 추정에 관한 연구

Curve Estimation among Citation and Centrality Measures in Article-level Citation Networks

  • 유소영 (연세대학교 문헌정보학과)
  • 투고 : 2012.05.30
  • 심사 : 2012.06.19
  • 발행 : 2012.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

이 연구에서는 인용 및 동시인용 문헌 네트워크에서의 중심성 지수를 사용한 추론 통계 적용의 첫 번째 단계로써 이들 간 관계의 선형성을 살펴보고자 하였다. 703개의 문헌 동시인용 네트워크를 활용하여 인용 빈도, 연결정도 중심성, 인접 중심성, 매개 중심성 간의 4가지 주요 관계의 패턴을 살펴본 결과, 모든 인용 및 중심성 간 관계가 선형모델보다는 비선형적 모델로 더 잘 설명될 수 있음을 통계적으로 확인되었다. 따라서 이들 간의 인과관계에 대한 다중회귀분석과 같은 추론 통계 분석의 기반이 되는 선형성을 확보하기 위해서는 논리적인 기준에 근거한 데이터 변환이나 실제값을 구간값으로 변환하는 과정이 필요하다고 할 수 있다.

The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.

키워드

참고문헌

  1. Bollen, J., Van de Sompel, H., Hagberg, A., & Chute, R. (2009). A Principal Component Analysis of 39 scientific impact measures. PLoS ONE, 4(6), e6022. http://dx.doi.org/10.1371/journal.pone.0006022
  2. Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H. D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5(3), 346-359. http://dx.doi.org/10.1016/j.joi.2011.01.006
  3. Burrell, Q. L. (2002). The nth-citation distribution and obsolescence. Scientometrics, 53, 309-323. http://dx.doi.org/10.1023/A:1014816911511
  4. Costas, R., van Leeuwen, T. N., & Bordons, M. (2010). A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact. Journal of the American Society for Information Science and Technology, 61(8), 1564-1581. http://dx.doi.org/10.1002/asi.21348
  5. de Solla Price, D. J. (1965). Networks of scientific papers. Science, 149, 510-515. https://doi.org/10.1126/science.149.3683.510
  6. de Solla Price, D. J. (1976). A general theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27, 292-306. https://doi.org/10.1002/asi.4630270505
  7. Garson, G.D. (2012). Curve Estimation. Quantitative Research in Public Administration, NC State University. Available from http://faculty.chass.ncsu.edu/garson/PA765/curve.htm
  8. Glanzel, W. (1992). On some stopping times of citation processes. Information Processing and Management, 28, 53-60. http://dx.doi.org/10.1016/0306-4573(92)90092-E
  9. Green, S., & Salkind, N. J. (2007). Using SPSS for Windows and Macintosh: Analyzing and Understanding Data(5th ed). New York, NY: Prentice Hall.
  10. Gupta, H. M., Campanha, J. R., & Pesce, R.A.G. (2005). Power-law distributions for the citation index of scientific publications and scientists. Brazilian Journal of Physics, 35(4A, December), 981-986. http://dx.doi.org/10.1590/S0103-97332005000600012
  11. Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215-239. https://doi.org/10.1016/0378-8733(78)90021-7
  12. Kim, Pan Jun, & Lee, Jae Yun (2010). A study on journal impact measurement with Hirsch-type indices. Journal of the Korean Society for Information Management, 27(1), 269-287. http://dx.doi.org/10.3743/KOSIM.2010.27.1.269
  13. Lee, Jae Yun (2011). A study on document citation indicators based on citation network analysis. Journal of the Korean Society for Library and Information Science, 45(2), 119-143. http://dx.doi.org/10.4275/KSLIS.2011.45.2.119
  14. Leydesdorff, L. (2009). How are new citation-based journal indicators adding to the bibliometric toolbox? Journal of the American Society for Information Science and Technology, 60(7), 1327-1336. http://dx.doi.org/10.1002/asi.v60:7
  15. Nadarajah, S., & Kotz, S. (2007). Models for citation behavior. Scientometrics, 72, 291-305. http://dx.doi.org/10.1007/s11192-007-1717-9
  16. Newman, M. E. J. (2003). The structure and function of complex networks. SIAM Review, 45(2), 167-256. http://dx.doi.org/10.1137/S003614450342480
  17. Nieminen, J. (1974). On the centrality in a graph. Scandinavian Journal of Psychology, 15(1), 332-336. http://dx.doi.org/10.1111/j.1467-9450.1974.tb00598.x
  18. Redner, S. (1998). How popular is your paper? An empirical study of the citation distribution. Eur Phys J B, 2, 131-134. https://doi.org/10.1007/s100510050233
  19. Redner, S. (2004). Citation statistics from more than a century of Physical Review. arXiv:physics/0407137.
  20. Rousseau, R. (1994). Double exponential models for first-citation processes. Scientometrics, 30, 213-227. http://dx.doi.org/10.1007/BF02017224
  21. Sabidussi, G. (1966). The centrality index of a graph. Psychometrika, 31(4), 581-603. https://doi.org/10.1007/BF02289527
  22. Simkin, M. V., & Vwani, P. R. (2007). A mathematical theory of citing. Journal of the American Society for Information Science and Technology, 58, 1661-1673. http://dx.doi.org/10.1002/asi.20653
  23. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Boston: Pearson/Allyn & Bacon.
  24. Yu, So Young (2012). Ascertaining the Characteristics of Centrality Measures in Citation Networks as Revealed by Their Relationship with Bibliometric Indices. (Doctoral dissertation). Yonsei University.
  25. Yu, So Young, & Lee, Jae Yun (2008). Journal citation analysis for library services on interdisciplinary domains: A case study of department of biotechnology, Y University. Journal of the Korean Society for Information Management, 25(4), 283-308. http://dx.doi.org/10.3743/KOSIM.2008.25.4.283 [Korean]

피인용 문헌

  1. Identifying the Research Fronts in Korean Library and Information Science by Document Co-citation Analysis vol.32, pp.4, 2015, https://doi.org/10.3743/KOSIM.2015.32.4.077