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An analysis of in-text citations based on fractional counting

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  • Pak, Chol Myong
  • Wang, Weibin
  • Yu, Guang

Abstract

With the development of citation analysis, the analysis of in-text citations is getting more important. There can be many references in the bibliography of a paper, but the way that each reference is mentioned within the full text of a paper is different. Some references are mentioned together with other references, and some references are mentioned alone. That is, a citation sentence can include only one reference or several references. However, the citation sentence gives readers a description. Thus, it is necessary to examine in-text citations by considering the way that each reference is mentioned within the full text. From this point of view, we introduce two counting methods (full counting and fractional counting) to examine in-text citations and compare the two counting methods. The number of in-text citations according to full counting was approximately 1.448 times larger than that according to fractional counting. The results show that the majority of in-text citations are independent, and the majority of references that have no independent mentions are mentioned only once. The results also show that most of the multiple mentioned references have high mention frequencies according to both full counting and fractional counting.

Suggested Citation

  • Pak, Chol Myong & Wang, Weibin & Yu, Guang, 2020. "An analysis of in-text citations based on fractional counting," Journal of Informetrics, Elsevier, vol. 14(4).
  • Handle: RePEc:eee:infome:v:14:y:2020:i:4:s1751157719301567
    DOI: 10.1016/j.joi.2020.101070
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    References listed on IDEAS

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    1. Gertrud Herlach, 1978. "Can retrieval of information from citation indexes be simplified? Multiple mention of a reference as a characteristic of the link between cited and citing article," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(6), pages 308-310, November.
    2. 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.
    3. CholMyong Pak & Guang Yu & Weibin Wang, 2018. "A study on the citation situation within the citing paper: citation distribution of references according to mention frequency," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 905-918, March.
    4. Dangzhi Zhao & Andreas Strotmann, 2016. "Dimensions and uncertainties of author citation rankings: Lessons learned from frequency-weighted in-text citation counting," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 671-682, March.
    5. Xiaojun Wan & Fang Liu, 2014. "WL-index: Leveraging citation mention number to quantify an individual's scientific impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(12), pages 2509-2517, December.
    6. Waltman, Ludo & van Eck, Nees Jan, 2015. "Field-normalized citation impact indicators and the choice of an appropriate counting method," Journal of Informetrics, Elsevier, vol. 9(4), pages 872-894.
    7. Xiaodan Zhu & Peter Turney & Daniel Lemire & André Vellino, 2015. "Measuring academic influence: Not all citations are equal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 408-427, February.
    8. Hu, Zhigang & Lin, Gege & Sun, Taian & Hou, Haiyan, 2017. "Understanding multiply mentioned references," Journal of Informetrics, Elsevier, vol. 11(4), pages 948-958.
    9. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
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