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Pennants for Garfield: bibliometrics and document retrieval

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  • Howard D. White

    (Drexel University)

Abstract

Eugene Garfield’s name, like that of any prolific author, can designate both an oeuvre and a person. That duality is explored here with pennant diagrams, a decade-old technique that can structure information about both oeuvres and persons in one scatterplot. Such diagrams are not readily made now, but may have a place in recommender systems of the future. This paper recapitulates the basics of creating and understanding them. In pennants, every term in a bibliometric distribution is weighted with a version of the TF * IDF formula from information retrieval. The distributions are generated by a seed term, such as a cited author’s name or a subject phrase, and consist of terms that co-occur with the seed in a database. TF * IDF orders the terms by relevance and specificity with respect to the seed—an outcome interpretable in light of relevance theory from linguistic pragmatics. Garfield’s name appears illustratively as a seed in one pennant and as a co-cited author in five others. Another example shows works by him and others that co-occur with the phrase “Citation Analysis” in Scisearch. Pennants are richly suggestive about authors, and here they are linked to a fruitful idea of Garfield’s that appeared in his first paper.

Suggested Citation

  • Howard D. White, 2018. "Pennants for Garfield: bibliometrics and document retrieval," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 757-778, February.
  • Handle: RePEc:spr:scient:v:114:y:2018:i:2:d:10.1007_s11192-017-2610-9
    DOI: 10.1007/s11192-017-2610-9
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    References listed on IDEAS

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    1. Michael H. MacRoberts & Barbara R. MacRoberts, 1989. "Problems of citation analysis: A critical review," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(5), pages 342-349, September.
    2. Eugene Garfield, 1997. "Validation of citation analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 48(10), pages 962-962, October.
    3. Stephen P. Harter, 1992. "Psychological relevance and information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 602-615, October.
    4. Howard D. White, 2010. "Some new tests of relevance theory in information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 653-667, June.
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    Cited by:

    1. Xinxin Wang & Zeshui Xu & Yong Qin, 2022. "Structure, trend and prospect of operational research: a scientific analysis for publications from 1952 to 2020 included in Web of Science database," Fuzzy Optimization and Decision Making, Springer, vol. 21(4), pages 649-672, December.
    2. Müge Akbulut & Yaşar Tonta & Howard D. White, 2020. "Related records retrieval and pennant retrieval: an exploratory case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 957-987, February.

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