Improving SCImago Journal & Country Rank (SJR) subject classification through reference analysis

Antonio J. Gómez-Núñez, Benjamín Vargas-Quesada, Félix de Moya-Anegón, Wolfgang Glänzel

Research output: Contribution to journalReview article

23 Citations (Scopus)

Abstract

In order to re-categorize the SCImago Journal & Country Rank (SJR) journals based on Scopus, as well as improve the SJR subject classification scheme, an iterative process built upon reference analysis of citing journals was designed. The first step entailed construction of a matrix containing citing journals and cited categories obtained through the aggregation of cited journals. Assuming that the most representative categories in each journal would be represented by the highest citation values regarding categories, the matrix vectors were reduced using a threshold to discern and discard the weakest relations. The process was refined on the basis of different parameters of a heuristic nature, including (1) the development of several tests applying different thresholds, (2) the designation of a cutoff, (3) the number of iterations to execute, and (4) a manual review operation of a certain amount of multi-categorized journals. Despite certain shortcomings related with journal classification, the method showed a solid performance in grouping journals at a level higher than categories-that is, aggregating journals into subject areas. It also enabled us to redesign the SJR classification scheme, providing for a more cohesive one that covers a good proportion of re-categorized journals.

Original languageEnglish
Pages (from-to)741-758
Number of pages18
JournalScientometrics
Volume89
Issue number3
DOIs
Publication statusPublished - Dec 1 2011

Keywords

  • Journal classification
  • Multidisciplinary databases
  • Reference analysis
  • SCImago Journal & Country Rank
  • Subject categorization

ASJC Scopus subject areas

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

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