Generating clustered journal maps: an automated system for hierarchical classification.

Autor/inn/en	Leydesdorff, Loet; Bornmann, Lutz; Wagner, Caroline S.
Titel	Generating clustered journal maps: an automated system for hierarchical classification.
Quelle	In: Scientometrics, (2017) 3, S.1601-1614 PDF als Volltext Verfügbarkeit
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0138-9130
DOI	10.1007/s11192-016-2226-5
Schlagwörter	Classification; Visualization; Journal; Scientific field; Citation; Decomposition
Abstract	Abstract Journal maps and classifications for 11,359 journals listed in the combined Journal Citation Reports 2015 of the Science and Social Sciences Citation Indexes are provided at https://leydesdorff.github.io/journals/ and http://www.leydesdorff.net/jcr15. A routine using VOSviewer for integrating the journal mapping and their hierarchical clusterings is also made available. In this short communication, we provide background on the journal mapping/clustering and an explanation about and instructions for the routine. We compare journal maps for 2015 with those for 2014 and show the delineations among fields and subfields to be sensitive to fluctuations. Labels for fields and sub-fields are not provided by the routine, but an analyst can add them for pragmatic or intellectual reasons. The routine provides a means of testing one’s assumptions against a baseline without claiming authority; clusters of related journals can be visualized to understand communities. The routine is generic and can be used for any 1-mode network.
Erfasst von	OLC
Update	2023/2/05