Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences &amp; Engineering (Cited-by Linking 데이터 기반 자연과학 및 공학 분야 학술논문 인용 패턴 분석)

Seo, Sun Kyung (서선경); Honam Choi (최호남); Byung-kyu Kim (김병규); Choi Seon Heui (최선희); Kim Jeong Hwan (김정환)

doi:10.3743/KOSIM.2016.33.2.157

Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences & Engineering

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2016, 33(2), pp.157~176
DOI : 10.3743/KOSIM.2016.33.2.157
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : May 23, 2016
Accepted : June 6, 2016
Published : June 30, 2016

Seo, Sun Kyung ¹, Honam Choi ¹, Byung-kyu Kim ², Choi Seon Heui ¹, Kim Jeong Hwan ¹

¹한국과학기술정보연구원
²KISTI

Accredited

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

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* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences & Engineering

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* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

Citing Pattern Analysis based on Cited-by Linking Data of DOI Journals in the Field of Natural Sciences & Engineering

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KEYWORDS

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