Construction of a Pragmatic Base Line for Journal Classifications and Maps Based on Aggregated Journal-Journal Citation Relations
Loet Leydesdorff, Lutz Bornmann, and Ping Zhou

TL;DR
This paper presents a new journal classification system based on aggregated citation data, creating a map of science that improves reproducibility and offers a hierarchical view of fields, exemplified with social sciences and information science.
Contribution
The paper introduces a pragmatic, tree-like classification system for journals using citation relations, enhancing reproducibility over existing algorithmic methods.
Findings
Developed a hierarchical classification with nine major fields.
Created maps of science at different levels of detail.
Addressed limitations in multi-disciplinary journal classification.
Abstract
A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category.…
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Taxonomy
TopicsBiomedical Text Mining and Ontologies · scientometrics and bibliometrics research · Advanced Text Analysis Techniques
