Can Scientific Journals be Classified in terms of Aggregated Journal-Journal Citation Relations using the Journal Citation Reports?

TL;DR

This paper explores classifying scientific journals based on aggregated citation data using factor analysis, highlighting the method's potential and limitations for journal classification.

Contribution

It demonstrates how factor analysis can be applied to journal citation data to test and refine journal classifications within the Science Citation Index.

Findings

Factor analysis reveals underlying structures in citation data.

Unrotated factor scores provide exact indicators of journal positions.

Classifications can be tested against database structures.

Abstract

The aggregated citation relations among journals included in the Science Citation Index provide us with a huge matrix which can be analyzed in various ways. Using principal component analysis or factor analysis, the factor scores can be used as indicators of the position of the cited journals in the citing dimensions of the database. Unrotated factor scores are exact, and the extraction of principal components can be made stepwise since the principal components are independent. Rotation may be needed for the designation, but in the rotated solution a model is assumed. This assumption can be legitimated on pragmatic or theoretical grounds. Since the resulting outcomes remain sensitive to the assumptions in the model, an unambiguous classification is no longer possible in this case. However, the factor-analytic solutions allow us to test classifications against the structures contained in the database. This will be demonstrated for the delineation of a set of biochemistry journals.