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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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