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

Abstract

This study introduces a new proposal to refine the classification of the SCImago Journal and Country Rank (SJR) platform by using clustering techniques and an alternative combination of citation measures from an initial 18,891 SJR journal network. Thus, a journal–journal matrix including simultaneously fractionalized values of direct citation, cocitation, and coupling was symmetrized by cosine similarity and later transformed into distances before performing clustering. The results provided a new cluster-based subject structure comprising 290 clusters that emerge by executing Ward's clustering in two phases and using a mixed labeling procedure based on tf-idf scores of the original SJR category tags and significant words extracted from journal titles. In total, 13,716 SJR journals were classified using this new cluster-based scheme. Although more than 5,000 journals were omitted in the classification process, the method produced a consistent classification with a balanced structure of coherent and well-defined clusters, a moderated multiassignment of journals, and a softer concentration of journals over clusters than in the original SJR categories. New subject disciplines such as “nanoscience and nanotechnology” or “social work” were also detected, providing evidence of good performance of our approach in refining the journal classification and updating the subject classification structure.