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Frequency and functional use of cited documents in information science

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  • Patricia A. Hooten

Abstract

The purpose of this study was to examine factors which may explain frequency and nature of use of documents in citing document texts over time. Articles published in the Journal of the American Society for Information Science in 1972, 1973, and 1974 were searched on SciSearch to derive two sample groups. One group was frequently cited; the other was infrequently cited. The functional uses of the sample document groups were examined by four classification taxonomies in 417 citing contexts. The patterns of frequency of use, multiple use, and functional use were examined over time. The citation levels of documents citing the two sample groups were examined as well. When measured by functional citation taxonomies, frequently and infrequently cited documents were not used for significantly different functions. Frequently cited documents, however, seemed more tightly linked (essential) than infrequently cited documents to the documents in which they were used. While frequently cited documents were not judged more useful than infrequently cited documents initially, they were used at a stable higher level over a longer period. Infrequently cited documents were used immediately following publication and then their use rapidly diminished. The repeated use of infrequently cited documents within documents tended to decrease over time while the repeated use of frequently cited documents tended to increase. Frequently cited articles were used for different functions in the period immediately following publication and a later time period. Infrequently cited articles were used with greater consistency in the two time periods. © 1991 John Wiley & Sons, Inc.

Suggested Citation

  • Patricia A. Hooten, 1991. "Frequency and functional use of cited documents in information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(6), pages 397-404, July.
  • Handle: RePEc:bla:jamest:v:42:y:1991:i:6:p:397-404
    DOI: 10.1002/(SICI)1097-4571(199107)42:63.0.CO;2-N
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    Cited by:

    1. Shengzhi Huang & Jiajia Qian & Yong Huang & Wei Lu & Yi Bu & Jinqing Yang & Qikai Cheng, 2022. "Disclosing the relationship between citation structure and future impact of a publication," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(7), pages 1025-1042, July.
    2. Liyue Chen & Jielan Ding & Vincent Larivière, 2022. "Measuring the citation context of national self‐references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(5), pages 671-686, May.
    3. Eugenio Petrovich, 2018. "Accumulation of knowledge in para-scientific areas: the case of analytic philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1123-1151, August.
    4. Boyack, Kevin W. & van Eck, Nees Jan & Colavizza, Giovanni & Waltman, Ludo, 2018. "Characterizing in-text citations in scientific articles: A large-scale analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 59-73.
    5. Sehrish Iqbal & Saeed-Ul Hassan & Naif Radi Aljohani & Salem Alelyani & Raheel Nawaz & Lutz Bornmann, 2021. "A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6551-6599, August.
    6. Naif Radi Aljohani & Ayman Fayoumi & Saeed-Ul Hassan, 2021. "An in-text citation classification predictive model for a scholarly search system," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5509-5529, July.

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