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Citation analysis using online databases: Feasibilities and shortcomings

Author

Listed:
  • Werner Marx

    (Max Planck Institute for Solid State Research)

  • Hermann Schier

    (Max Planck Institute for Solid State Research)

  • Michael Wanitschek

    (Max Planck Institute for Solid State Research)

Abstract

Extensive citation analysis with the Science Citation Index (SCI) has become possible through expanded search capabilities introduced by STN International a few years ago. STN enhanced its retrieval language with some important features, originally developed for statistical analysis of patents. Most important are an expanded select command and several functions to list the search results. The publications to be evaluated may be selected either in the SCI, or in a number of other bibliographic databases offered by the host. With the help of these features, the basic methods to appropriately measure the impact of scientific activities are demonstrated. Furthermore, possible shortcomings as well as the risks when interpreting the results of such studies are discussed.

Suggested Citation

  • Werner Marx & Hermann Schier & Michael Wanitschek, 2001. "Citation analysis using online databases: Feasibilities and shortcomings," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(1), pages 59-82, September.
    • Handle: RePEc:spr:scient:v:52:y:2001:i:1:d:10.1023_a:1012798911792
    DOI: 10.1023/A:1012798911792
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    References listed on IDEAS

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    1. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
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    Cited by:

    1. Christoph Neuhaus & Andreas Litscher & Hans-Dieter Daniel, 2007. "Using scripts to streamline citation analysis on STN International," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(1), pages 145-150, April.
    2. Selçuk Bilir & Ersin Göğüş & Özgecan Önal & Nazlı Derya Öztürkmen & Talar Yontan, 2013. "Research performance of Turkish astronomers in the period of 1980–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 477-489, November.
    3. William W. Hood & Concepción S. Wilson, 2003. "Informetric studies using databases: Opportunities and challenges," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 587-608, November.
    4. Barbosa, Fabiana G. & Schneck, Fabiana, 2015. "Characteristics of the top-cited papers in species distribution predictive models," Ecological Modelling, Elsevier, vol. 313(C), pages 77-83.
    5. Mallig, Nicolai, 2010. "A relational database for bibliometric analysis," Journal of Informetrics, Elsevier, vol. 4(4), pages 564-580.
    6. Mallig, Nicolai, 2010. "A relational database for bibliometric analysis," Discussion Papers "Innovation Systems and Policy Analysis" 22, Fraunhofer Institute for Systems and Innovation Research (ISI).
    7. Guan Jiancheng & Wang Junxia, 2004. "Evaluation and interpretation of knowledge production efficiency," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(1), pages 131-155, January.
    8. Christoph Neuhaus & Hans-Dieter Daniel, 2009. "A new reference standard for citation analysis in chemistry and related fields based on the sections of Chemical Abstracts," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(2), pages 219-229, February.
    9. Candan Gokceoglu & Aral I. Okay & Ebru Sezer, 2008. "International earth science literature from Turkey — 1970–2005: Trends and possible causes," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(3), pages 409-423, March.
    10. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    11. Marilyn H Oermann & Julia Shaw‐Kokot & George J Knafl & Jo Dowell, 2010. "Dissemination of research into clinical nursing literature," Journal of Clinical Nursing, John Wiley & Sons, vol. 19(23‐24), pages 3435-3442, December.

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