IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v7y2013i4p887-896.html
   My bibliography  Save this article

Where are citations located in the body of scientific articles? A study of the distributions of citation locations

Author

Listed:
  • Hu, Zhigang
  • Chen, Chaomei
  • Liu, Zeyuan

Abstract

We address issues concerning what one may learn from how citation instances are distributed in scientific articles. We visualize and analyze patterns of citation distributions in the full text of 350 articles published in the Journal of Informetrics. In particular, we visualize and analyze the distributions of citations in articles that are organized in a commonly seen four-section structure, namely, introduction, method, results, and conclusions (IMRC). We examine the locations of citations to the groundbreaking h-index paper by Hirsch in 2005 and how patterns associated with citation locations evolve over time. The results show that citations are highly concentrated in the first section of an article. The density of citations in the first section is about three times higher than that in subsequent sections. The distributions of citations to highly cited papers are even more uneven.

Suggested Citation

  • Hu, Zhigang & Chen, Chaomei & Liu, Zeyuan, 2013. "Where are citations located in the body of scientific articles? A study of the distributions of citation locations," Journal of Informetrics, Elsevier, vol. 7(4), pages 887-896.
  • Handle: RePEc:eee:infome:v:7:y:2013:i:4:p:887-896
    DOI: 10.1016/j.joi.2013.08.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157713000692
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joi.2013.08.005?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.

    References listed on IDEAS

    as
    1. Ding, Ying & Liu, Xiaozhong & Guo, Chun & Cronin, Blaise, 2013. "The distribution of references across texts: Some implications for citation analysis," Journal of Informetrics, Elsevier, vol. 7(3), pages 583-592.
    2. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    3. Terrence A. Brooks, 1986. "Evidence of complex citer motivations," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 37(1), pages 34-36, January.
    4. Terrence A. Brooks, 1985. "Private acts and public objects: An investigation of citer motivations," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 36(4), pages 223-229, July.
    5. V. Cano, 1989. "Citation behavior: Classification, utility, and location," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(4), pages 284-290, July.
    6. Shengbo Liu & Chaomei Chen, 2013. "The differences between latent topics in abstracts and citation contexts of citing papers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(3), pages 627-639, March.
    7. Leo Egghe & Ronald Rousseau, 2006. "An informetric model for the Hirsch-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 121-129, October.
    8. Henry Small, 2011. "Interpreting maps of science using citation context sentiments: a preliminary investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 373-388, May.
    9. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    10. Shengbo Liu & Chaomei Chen, 2013. "The differences between latent topics in abstracts and citation contexts of citing papers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(3), pages 627-639, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bikun Chen & Dannan Deng & Zhouyan Zhong & Chengzhi Zhang, 2020. "Exploring linguistic characteristics of highly browsed and downloaded academic articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1769-1790, March.
    2. 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.
    3. 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.
    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. Hoyeop Lee & Jueun Kwak & Min Song & Chang Ouk Kim, 2015. "Coherence analysis of research and education using topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1119-1137, February.
    6. Bornmann, Lutz & Marx, Werner, 2012. "HistCite analysis of papers constituting the h index research front," Journal of Informetrics, Elsevier, vol. 6(2), pages 285-288.
    7. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    8. Chao Lu & Ying Ding & Chengzhi Zhang, 2017. "Understanding the impact change of a highly cited article: a content-based citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 927-945, August.
    9. Stremersch, Stefan & Camacho, Nuno & Vanneste, Sofie & Verniers, Isabel, 2015. "Unraveling scientific impact: Citation types in marketing journals," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 64-77.
    10. S. Alonso & F. J. Cabrerizo & E. Herrera-Viedma & F. Herrera, 2010. "hg-index: a new index to characterize the scientific output of researchers based on the h- and g-indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 391-400, February.
    11. Franceschini, Fiorenzo & Maisano, Domenico, 2010. "The citation triad: An overview of a scientist's publication output based on Ferrers diagrams," Journal of Informetrics, Elsevier, vol. 4(4), pages 503-511.
    12. van Eck, Nees Jan & Waltman, Ludo, 2008. "Generalizing the h- and g-indices," Journal of Informetrics, Elsevier, vol. 2(4), pages 263-271.
    13. Filippo Radicchi & Claudio Castellano, 2013. "Analysis of bibliometric indicators for individual scholars in a large data set," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 627-637, December.
    14. van Eck, N.J.P. & Waltman, L., 2008. "Generalizing the h- and g-indices," ERIM Report Series Research in Management ERS-2008-049-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    15. Lina Zhou & Uchechukwuka Amadi & Dongsong Zhang, 2020. "Is Self-Citation Biased? An Investigation via the Lens of Citation Polarity, Density, and Location," Information Systems Frontiers, Springer, vol. 22(1), pages 77-90, February.
    16. Elizabeth S. Vieira & José A. N. F. Gomes, 2011. "An impact indicator for researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 607-629, November.
    17. Ruhao Zhang & Junpeng Yuan, 2022. "Enhanced author bibliographic coupling analysis using semantic and syntactic citation information," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7681-7706, December.
    18. Zhang, Lin & Thijs, Bart & Glänzel, Wolfgang, 2011. "The diffusion of H-related literature," Journal of Informetrics, Elsevier, vol. 5(4), pages 583-593.
    19. John Panaretos & Chrisovaladis Malesios, 2009. "Assessing scientific research performance and impact with single indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 635-670, December.
    20. Raja Habib & Muhammad Tanvir Afzal, 2019. "Sections-based bibliographic coupling for research paper recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 643-656, May.

    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:7:y:2013:i:4:p:887-896. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.