Updating the SCImago journal and country rank classification: A new approach using Ward's clustering and alternative combination of citation measures

Journal of the Association for Information Science and Technology

Volumn 67, Issue 1, 2016, Pages 178-190

  Gómez Núñez, Antonio J ^a   Vargas Quesada, Benjamín ^b   de Moya Anegón, Félix ^a  

^a CSIC   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

bibliometrics; classification

Indexed keywords

CLASSIFICATION (OF INFORMATION);

BALANCED STRUCTURES; BIBLIOMETRICS; CLASSIFICATION PROCESS; CLUSTERING TECHNIQUES; LABELING PROCEDURES; NANOSCIENCE AND NANOTECHNOLOGIES; SUBJECT CLASSIFICATION; WARD'S CLUSTERING;

NANOSCIENCE;

BIBLIOMETRICS; CLASSIFICATION; HUMAN;

EID: 84975029652     PISSN: 23301635     EISSN: 23301643     Source Type: Journal    
DOI: 10.1002/asi.23370     Document Type: Article

References (46)

1. Bassecoulard, E., & Zitt, M. (1999). Indicators in a research institute: A multilevel classification of journals. Scientometrics, 44(3), 323–345.
2. Bichteler, J., & Parsons, R.G. (1974). Document retrieval by means of an automatic classification algorithm for citations. Information Storage and Retrieval, 10(7–8), 267–278.
3. Boyack, K.W., Klavans, R., & Börner, K. (2005). Mapping the backbone of science. Scientometrics, 64(3), 351–374.
4. Carpenter, M.P., & Narin, F. (1973). Clustering of scientific journals. Journal of the American Society for Information Science, 24(6), 425–436.
5. Chen, C.M. (2008). Classification of scientific networks using aggregated journal-journal citation relations in the journal citation reports. Journal of the American Society for Information Science and Technology, 59(14), 2296–2304.
6. Cormack, R.M. (1971). A review of classification. Journal of the Royal Statistical Society. Series A (General), 134(3), 321–367.
7. Croft, W.B. (1980). A model of cluster searching based on classification. Information systems, 5(3), 189–195.
8. Elsevier (2014). Subject area categories of Scopus. Retrieved from http://help.scopus.com/Content/h_subject_categories.htm
9. Everitt, B.S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.). London: Wiley.
10. Garfield, E. (1975). Clusters and classification. Essays of an Information Scientist, 2, 354–355.
11. Garfield, E., Malin, M.V., & Small, H. (1975). A system for automatic classification of scientific literature. Journal of the Indian Institute of Science, 57(2), 61–74.
12. Glänzel, W., & Schubert, A. (2003). A new classification scheme of science fields and subfields designed for scientometric evaluation purposes. Scientometrics, 56(3), 357–367.
13. Glänzel, W., & Thijs, B. (2012). Using “core documents” for detecting and labelling new emerging topics. Scientometrics, 91(2), 399–416.
14. Glenisson, P., Glänzel, W., & Persson, O. (2005). Combining full-text analysis and bibliometric indicators. A pilot study. Scientometrics, 63(1), 163–180.
15. Gómez, I., Bordons, M., Fernández, M.T., & Méndez, A. (1996). Coping with the problem of subject classification diversity. Scientometrics, 35(2), 223–235.
16. Gómez-Núñez, A.J., Vargas-Quesada, B., Moya-Anegón, F., & Glänzel, W. (2011). Improving SCImago Journal & Country Rank (SJR) subject classification through reference analysis. Scientometrics, 89(3), 741–758.
17. Gómez-Núñez, A.J., Batagelj, V., Vargas-Quesada, B., Moya-Anegón, F., & Chinchilla-Rodríguez, Z. (2014). Optimising SCImago Journal & Country Rank classification by community detection. Journal of Informetrics, 8(2), 369–383.
18. He, Q. (1999). A review of clustering algorithms as applied to IR (doctoral dissertation). Univ. Illinois at Urbana-Champaign, Tech. Rep. UIUCLIS-1999/6 + IRG.
19. Janssens, F., Zhang, L., De Moor, B., & Glänzel, W. (2009). Hybrid clustering for validation and improvement of subject-classification schemes. Information Processing and Management, 45(6), 683–702.
20. Klavans, R., & Boyack, K.W. (2007). Is there a convergent structure of science? A comparison of maps using the ISI and Scopus databases. In D. Torres-Salinas & H. Moed (Eds.), Proceedings of the 11th International Conference of the International Society for Scientometrics and Informetrics (pp. 437–448). Madrid, Spain: ISSI.
21. Klavans, R., & Boyack, K.W. (2009). Toward a consensus map of science. Journal of the American Society for Information Science and Technology, 60(3), 455–476.
22. Leydesdorff, L. (2002). Dynamic and evolutionary updates of classificatory schemes in scientific journal structures. Journal of the American Society for Information Science and Technology, 53(12), 987–994.
23. Leydesdorff, L., & Rafols, I. (2009). A global map of science based on the ISI subject categories. Journal of the American Society for Information Science and Technology, 60(2), 348–362.
24. Leydesdorff, L., Moya-Anegón, F., & Guerrero-Bote, V.P. (2010). Journal maps on the basis of Scopus data: A comparison with the journal citation reports of the ISI. Journal of the American Society for Information Science and Technology, 61(2), 352–369.
25. Moya-Anegón, F., Vargas-Quesada, B., Herrero-Solana, V., Chinchilla-Rodríguez, Z., Corera-Álvarez, E., & Munoz-Fernández, F.J. (2004). A new technique for building maps of large scientific domains based on the cocitation of classes and categories. Scientometrics, 61(1), 129–145.
26. Moya-Anegón, F., Vargas-Quesada, B., Chinchilla-Rodríguez, Z., Corera-Álvarez, E., Gonzalez-Molina, A., Munoz-Fernández, F.J. & Herrero-Solana, V. (2007). Visualizing the marrow of science. Journal of the American Society for Information Science and Technology, 58(14), 2167–2179.
27. Narin, F. (1976). Evaluative bibliometrics: The use of publication and citation analysis in the evaluation of scientific activity. Fair Lawn, NJ: Computer Horizons.
28. Persson, O. (2010). Identifying research themes with weighted direct citation links. Journal of Informetrics, 4(3), 415–422.
29. Price, D.J.D. (1963). Little science, big science. New York: Columbia University Press.
30. Price, N., & Schiminovich, S. (1968). A clustering experiment: First step towards a computer-generated classification scheme. Information Storage and Retrieval, 4(3), 271–280.
31. Rafols, I., & Leydesdorff, L. (2009). Content-based and algorithmic classifications of journals: Perspectives on the dynamics of scientific communication and indexer effects. Journal of the American Society for Information Science and Technology, 60(9), 1823–1835.
32. Rousseau, R., & Zuccala, A. (2004). A classification of author co-citations: Definitions and search strategies. Journal of the American Society for Information Science and Technology, 55(6), 513–629.
33. Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24(5), 513–523.
34. Schiminovich, S. (1971). Automatic classification and retrieval of documents by means of a bibliographic pattern discovery algorithm. Information Storage and Retrieval, 6(6), 417–435.
35. SCImago. (2007). SCImago Journal & Country Rank. Retrieved from http://www.scimagojr.com/
36. Small, H., & Garfield, E. (1985). The geography of science: Disciplinary and national mappings. Journal of Information Science, 11(4), 147–159.
37. Small, H., & Griffith, B.C. (1974). The structure of scientific literatures I: Identifying and graphing specialties. Science Studies, 4(1), 17–40.
38. Small, H., & Sweeney, E. (1985). Clustering the science citation index using co-citations I. A comparison of methods. Scientometrics, 7(3–6), 391–409.
39. Small, H., Sweeney, E., & Greenlee, E. (1985). Clustering the science citation index using co-citations II. Mapping science. Scientometrics, 8(5–6), 321–340.
40. van Rijsbergen, C.J. (1974). Further experiments with hierarchic clustering in document retrieval. Information Storage and Retrieval, 10(1), 1–14.
41. van Rijsbergen, C.J., & Croft, W.B. (1975). Document clustering: An evaluation of some experiments with the Cranfield 1,400 collection. Information Processing and Management, 11, 171–182.
42. Vargas-Quesada, B., & Moya-Anegón, F. (2007). Visualizing the structure of science. Berlin: Springer.
43. Wild, F. (2011). lsa: Latent semantic analysis. R package version 0.63-3. Retrieved from http://cran.r-project.org/web/packages/lsa/index.html
44. Willett, P. (1988). Recent trends in hierarchic document clustering: A critical review. Information Processing and Management, 24(5), 517–597.
45. Yagi, E., Badash, L., & Beaver, D.B. (1996). Derek J. de S. Price (1922–83): Historian of science and herald of scientometrics. Interdisciplinary Science Reviews, 21(1), 64–84.
46. Zhang, L., Janssens, F., Liang, L., & Glänzel, W. (2010). Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research. Scientometrics, 82(3), 687–706.