IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v13y2019i2p658-678.html
   My bibliography  Save this article

Should citations be counted separately from each originating section?

Author

Listed:
  • Thelwall, Mike

Abstract

Articles are cited for different purposes and differentiating between reasons when counting citations may therefore give finer-grained citation count information. Although identifying and aggregating the individual reasons for each citation may be impractical, recording the number of citations that originate from different article sections might illuminate the general reasons behind a citation count (e.g., 110 citations = 10 Introduction citations + 100 Methods citations). To help investigate whether this could be a practical and universal solution, this article compares 19 million citations with DOIs from six different standard sections in 799,055 PubMed Central open access articles across 21 out of 22 fields. There are apparently non-systematic differences between fields in the most citing sections and the extent to which citations from one section overlap with citations from another, with some degree of overlap in most cases. Thus, at a science-wide level, section headings are partly unreliable indicators of citation context, even if they are more standard within individual fields. They may still be used within fields to help identify individual highly cited articles that have had one type of impact, especially methodological (Methods) or context setting (Introduction), but expert judgement is needed to validate the results.

Suggested Citation

  • Thelwall, Mike, 2019. "Should citations be counted separately from each originating section?," Journal of Informetrics, Elsevier, vol. 13(2), pages 658-678.
  • Handle: RePEc:eee:infome:v:13:y:2019:i:2:p:658-678
    DOI: 10.1016/j.joi.2019.03.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157718305121
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joi.2019.03.009?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    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. 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.
    3. 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.
    4. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2023. "Context-aware citation recommendation of scientific papers: comparative study, gaps and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4243-4268, August.
    5. Dongqing Lyu & Xuanmin Ruan & Juan Xie & Ying Cheng, 2021. "The classification of citing motivations: a meta-synthesis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3243-3264, April.
    6. Kayvan Kousha & Mike Thelwall & Matthew Bickley, 2022. "The high scholarly value of grey literature before and during Covid-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3489-3504, June.
    7. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    8. Zhang, Chengzhi & Liu, Lifan & Wang, Yuzhuo, 2021. "Characterizing references from different disciplines: A perspective of citation content analysis," Journal of Informetrics, Elsevier, vol. 15(2).

    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:eee:infome:v:13:y:2019:i:2:p:658-678. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.