A new methodology for constructing a publication-level classification system of science.
Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification s...
| Published in: | Journal of the American Society for Information Science & Technology Vol. 63; no. 12; pp. 2378 - 2393 |
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| Main Authors: | , |
| Format: | algorithm equations & formulas research tables/charts Journal Article |
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Wiley-Blackwell
Dec2012
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104441438&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104441438 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15322882 IGD jtl: Journal of the American Society for Information Science & Technology issn: 15322882 maglogo: Y pubinfo: dt: Dec2012 vid: 63 iid: 12 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104441438 83731223 10.1002/asi.22748 104441438 ppf: 2378 ppct: 15 formats: tig: atl: A new methodology for constructing a publication-level classification system of science. aug: au: Waltman, Ludo Eck, Nees Jan affil: Centre for Science and Technology Studies, Leiden University sug: subj: Serial Publications Science Classification Bibliometrics Human Data Analysis Software Reference Databases Information Science Organizations United States ab: Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification systems have two important limitations: They offer only a limited amount of detail, and they have difficulties with multidisciplinary journals. To avoid these limitations, we introduce a new methodology for constructing classification systems at the level of individual publications. In the proposed methodology, publications are clustered into research areas based on citation relations. The methodology is able to deal with very large numbers of publications. We present an application in which a classification system is produced that includes almost 10 million publications. Based on an extensive analysis of this classification system, we discuss the strengths and the limitations of the proposed methodology. Important strengths are the transparency and relative simplicity of the methodology and its fairly modest computing and memory requirements. The main limitation of the methodology is its exclusive reliance on direct citation relations between publications. The accuracy of the methodology can probably be increased by also taking into account other types of relations-for instance, based on bibliographic coupling. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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