Generating clustered journal maps: an automated system for hierarchical classification
Issue Date:
2017-01-03Metadata
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Springer NetherlandsCitation:
Leydesdorff, L., Bornmann, L., & Wagner, C. S. (2017). Generating clustered journal maps: an automated system for hierarchical classification. Scientometrics, 110(3), 1601-1614. https://doi.org/10.1007/s11192-016-2226-5Abstract:
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.
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ArticleRights:
© The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Items in Knowledge Bank are protected by copyright, with all rights reserved, unless otherwise indicated.