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Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences & Engineering
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 Title & Authors
Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences & Engineering
Seo, Sun Kyung; Choi, Ho Nam; Kim, Byung-Kyu; Choi, Seon-Heui; Kim, Jeong Hwan;
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 Abstract
Cited-by Linking Service is one of the CrossRef`s information services that allows you to discover how your publications are being cited and to incorporate that information into your online publication platform. This study tries to investigate citation patterns in the field of both Natural Science and Engineering using all of DOI assigned articles and Cited-by Linking data which are accumulated and managed by KISTI. The investigating approach is designed to verify the theory of 1) cognitive accessibility, 2) `perceived quality and significance` and 3) `subject relativity`. For cognitive accessibility verification the fulltext language portion of Korean and English between "Cited DOI Source Data" and "NOT Cited DOI Source Data" was compared. For perceived quality and significance verification the availability of the "Cited DOI Source Data" and "NOT Cited DOI Source Data" from SCIE and SCOPUS was employed. For subject relativity DOI data were classified and analysed on the basis of OECD subject classification scheme. Findings are that global citability is closely related to the fulltext language of the articles and their quality and significance. And in the natural science field most of citations are from the same subject categories, while relatively more citations are from other subject categories in the engineering field.
 Keywords
citing pattern analysis;Cited-by Linking Data;DOI articles;
 Language
Korean
 Cited by
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