Research on citation mention times and contributions using a neural network

Weibin Wang, Zheng Wang, Tian Yu, CholMyong Pak and Guang Yu ()
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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

Scientometrics, 2020, vol. 125, issue 3, No 22, 2383-2400

Abstract: 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.

Keywords: Citation mention times; Neural network; Generalised Pareto distribution; Contribution (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:125:y:2020:i:3:d:10.1007_s11192-020-03711-2

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DOI: 10.1007/s11192-020-03711-2

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