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Research on citation mention times and contributions using a neural network

Author

Listed:
  • Weibin Wang

    (Harbin Institute of Technology)

  • Zheng Wang

    (Chongqing Technology and Business University)

  • Tian Yu

    (Harbin Engineering University)

  • CholMyong Pak

    (Harbin Institute of Technology)

  • Guang Yu

    (Harbin Institute of Technology)

Abstract

With the development of citation analysis, citation mention times are drawing more attention. Aiming to extract mention times more conveniently and quickly, this study focused on developing a high-accuracy citation recognition algorithm based on neural networks, thereby providing automatic extraction of the number of citation mentions in citing papers, and on assessing its performance in PDF papers with different citation styles. We also used this algorithm to study the distribution rule and contribution of citations to citing papers. The results showed that the proposed algorithm is feasible for use in citation-mention-related research and further verified that the statistical distribution of the number of citation mentions conforms to the generalised Pareto distribution. Meanwhile, references mentioned more than twice accounted for about 20–40% of the total and contributed more than other references.

Suggested Citation

  • Weibin Wang & Zheng Wang & Tian Yu & CholMyong Pak & Guang Yu, 2020. "Research on citation mention times and contributions using a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2383-2400, December.
    • Handle: RePEc:spr:scient:v:125:y:2020:i:3:d:10.1007_s11192-020-03711-2
    DOI: 10.1007/s11192-020-03711-2
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    References listed on IDEAS

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    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. Marc Bertin & Iana Atanassova & Yves Gingras & Vincent Larivière, 2016. "The invariant distribution of references in scientific articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 164-177, January.
    3. 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.
    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. 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.
    6. 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.
    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. Ronald Rousseau, 2005. "Median and percentile impact factors: A set of new indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(3), pages 431-441, June.
    9. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    10. E. Garfield & I. H. Sher, 1963. "New factors in the evaluation of scientific literature through citation indexing," American Documentation, Wiley Blackwell, vol. 14(3), pages 195-201, July.
    11. 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.
    12. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S., 2013. "Some modifications to the SNIP journal impact indicator," Journal of Informetrics, Elsevier, vol. 7(2), pages 272-285.
    13. Mingyang Wang & Shijia Jiao & Kah-Hin Chai & Guangsheng Chen, 2019. "Building journal’s long-term impact: using indicators detected from the sustained active articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 261-283, October.
    14. 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.
    15. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    16. González-Pereira, Borja & Guerrero-Bote, Vicente P. & Moya-Anegón, Félix, 2010. "A new approach to the metric of journals’ scientific prestige: The SJR indicator," Journal of Informetrics, Elsevier, vol. 4(3), pages 379-391.
    17. Hu, Zhigang & Lin, Gege & Sun, Taian & Hou, Haiyan, 2017. "Understanding multiply mentioned references," Journal of Informetrics, Elsevier, vol. 11(4), pages 948-958.
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