IDEAS home Printed from https://ideas.repec.org/a/bla/jamest/v33y1982i4p208-216.html
   My bibliography  Save this article

Characteristics of a Literature as Predictors of Relatedness Between Cited and Citing Works

Author

Listed:
  • Susan Bonzi

Abstract

A preliminary investigation was conducted to explore which characteristics of citing and cited works may aid in determining relatedness between documents. Thirteen variables were tested on 31 library/information science articles containing nearly 500 citations. Analysis indicates that source of cited work, source of citing work, number of times a work is cited in text, and type of citing article show promise of predicting relatedness between citing and cited works.

Suggested Citation

  • Susan Bonzi, 1982. "Characteristics of a Literature as Predictors of Relatedness Between Cited and Citing Works," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 33(4), pages 208-216, July.
  • Handle: RePEc:bla:jamest:v:33:y:1982:i:4:p:208-216
    DOI: 10.1002/asi.4630330404
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.4630330404
    Download Restriction: no

    File URL: https://libkey.io/10.1002/asi.4630330404?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Han & Martin, Eric & Mahidadia, Ashesh, 2014. "Contents and time sensitive document ranking of scientific literature," Journal of Informetrics, Elsevier, vol. 8(3), pages 546-561.
    2. Faiza Qayyum & Harun Jamil & Naeem Iqbal & DoHyeun Kim & Muhammad Tanvir Afzal, 2022. "Toward potential hybrid features evaluation using MLP-ANN binary classification model to tackle meaningful citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6471-6499, November.
    3. Faiza Qayyum & Muhammad Tanvir Afzal, 2019. "Identification of important citations by exploiting research articles’ metadata and cue-terms from content," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 21-43, January.
    4. Dangzhi Zhao & Andreas Strotmann, 2020. "Deep and narrow impact: introducing location filtered citation counting," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 503-517, January.
    5. Dangzhi Zhao & Andreas Strotmann, 2020. "Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 255-270, July.
    6. Huang, Chen-Hao & Liu, John S. & Ho, Mei Hsiu-Ching & Chou, Tzu-Chuan, 2022. "Towards more convergent main paths: A relevance-based approach," Journal of Informetrics, Elsevier, vol. 16(3).
    7. Saeed-Ul Hassan & Iqra Safder & Anam Akram & Faisal Kamiran, 2018. "A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 973-996, August.
    8. 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.
    9. Heng Huang & Donghua Zhu & Xuefeng Wang, 2022. "Evaluating scientific impact of publications: combining citation polarity and purpose," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5257-5281, September.
    10. Tahamtan, Iman & Bornmann, Lutz, 2018. "Core elements in the process of citing publications: Conceptual overview of the literature," Journal of Informetrics, Elsevier, vol. 12(1), pages 203-216.
    11. Aurora González-Teruel & Francisca Abad-García, 2018. "The influence of Elfreda Chatman’s theories: a citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1793-1819, December.
    12. Zehra Taşkın & Umut Al, 2018. "A content-based citation analysis study based on text categorization," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 335-357, January.
    13. 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.
    14. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jamest:v:33:y:1982:i:4:p:208-216. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.