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Combining commercial citation indexes and open-access bibliographic databases to delimit highly interdisciplinary research fields for citation analysis

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  • Strotmann, Andreas
  • Zhao, Dangzhi

Abstract

Field delimitation for citation analysis, the process of collecting a set of bibliographic records with cited-reference information of research articles that represent a research field, is the first step in any citation analysis study of a research field. Due to a number of limitations, the commercial citation indexes have long made it difficult to obtain a comprehensive dataset in this step. This paper discusses some of the limitations imposed by these databases, and reports on a method to overcome some of these limitations that was used with great success to delimit an emerging and highly interdisciplinary biomedical research field, stem cell research. The resulting field delimitation and the citation network it induces are both excellent. This multi-database method relies on using PubMed for the actual field delimitation, and on mapping between Scopus and PubMed records for obtaining comprehensive information about cited-references contained in the resulting literature. This method provides high-quality field delimitations for citation studies that can be used as benchmarks for studies of the impact of data collection biases on citation metrics, and may help improve confidence in results of scientometric studies for an increased impact of scientometrics on research policy.

Suggested Citation

  • Strotmann, Andreas & Zhao, Dangzhi, 2010. "Combining commercial citation indexes and open-access bibliographic databases to delimit highly interdisciplinary research fields for citation analysis," Journal of Informetrics, Elsevier, vol. 4(2), pages 194-200.
    • Handle: RePEc:eee:infome:v:4:y:2010:i:2:p:194-200
    DOI: 10.1016/j.joi.2009.12.001
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    References listed on IDEAS

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    1. Peter Ingwersen & Finn Hjortgaard Christensen, 1997. "Data set isolation for bibliometric online analyses of research publications: Fundamental methodological issues," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 48(3), pages 205-217, March.
    2. Olle Persson, 2001. "All author citations versus first author citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(2), pages 339-344, February.
    3. Zhao, Dangzhi & Strotmann, Andreas, 2008. "Comparing all-author and first-author co-citation analyses of information science," Journal of Informetrics, Elsevier, vol. 2(3), pages 229-239.
    4. Jesper W. Schneider & Birger Larsen & Peter Ingwersen, 2009. "A comparative study of first and all-author co-citation counting, and two different matrix generation approaches applied for author co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 103-130, July.
    5. Jian Qin, 2000. "Semantic similarities between a keyword database and a controlled vocabulary database: An investigation in the antibiotic resistance literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(2), pages 166-180.
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    Citations

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    Cited by:

    1. Lutz Bornmann & Klaus Wohlrabe, 2019. "Normalisation of citation impact in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 841-884, August.
    2. Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Bornmann, Lutz & Haunschild, Robin, 2022. "Empirical analysis of recent temporal dynamics of research fields: Annual publications in chemistry and related areas as an example," Journal of Informetrics, Elsevier, vol. 16(2).
    4. Colliander, Cristian & Ahlgren, Per, 2011. "The effects and their stability of field normalization baseline on relative performance with respect to citation impact: A case study of 20 natural science departments," Journal of Informetrics, Elsevier, vol. 5(1), pages 101-113.
    5. Tomaz Bartol & Karmen Stopar, 2015. "Nano language and distribution of article title terms according to power laws," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 435-451, May.
    6. Dangzhi Zhao & Andreas Strotmann, 2011. "Intellectual structure of stem cell research: a comprehensive author co-citation analysis of a highly collaborative and multidisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 115-131, April.
    7. Haunschild, Robin & Daniels, Angela D. & Bornmann, Lutz, 2022. "Scores of a specific field-normalized indicator calculated with different approaches of field-categorization: Are the scores different or similar?," Journal of Informetrics, Elsevier, vol. 16(1).
    8. Bornmann, Lutz & Haunschild, Robin, 2016. "Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator," Journal of Informetrics, Elsevier, vol. 10(3), pages 875-887.

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