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Analysis of the relationships among paper citation and its influencing factors: a Bayesian network-based approach

Author

Listed:
  • Mingyue Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Tingcan Ma

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Lewei Zhou

    (Chinese Academy of Sciences)

  • Mingliang Yue

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

The broad use of citations as evaluation basis has prompted the academic community to think about the mechanism of citations. In this paper, we propose a Bayesian network-based method for the analysis of the relationships among paper citation and its influencing factors. We investigate the factors that may be related to paper citation, calculate the factor values and determine the factor states. Then we design an amended K2 algorithm for Bayesian network structure learning to handle the situation that no strict sort exists among factors. At last, we use Bayesian network inference to analyse the relationships among paper citation and the influencing factors and present certain interesting findings. We believe the method can provide scholars with new intelligence analysis approach, either for citation analysis or other related issues like talent analysis, research areas analysis, and others.

Suggested Citation

  • Mingyue Sun & Tingcan Ma & Lewei Zhou & Mingliang Yue, 2023. "Analysis of the relationships among paper citation and its influencing factors: a Bayesian network-based approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3017-3033, May.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04697-3
    DOI: 10.1007/s11192-023-04697-3
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    References listed on IDEAS

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    More about this item

    Keywords

    Citations analysis; Bayesian network; Influencing factors; Amended K2 algorithm;
    All these keywords.

    JEL classification:

    • K2 - Law and Economics - - Regulation and Business Law

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