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Discovery of factors influencing citation impact based on a soft fuzzy rough set model

Author

Listed:
  • Mingyang Wang

    (Northeast Forestry University
    Harbin Institute of Technology)

  • Guang Yu

    (Harbin Institute of Technology)

  • Shuang An

    (Harbin Institute of Technology)

  • Daren Yu

    (Harbin Institute of Technology)

Abstract

In this paper, the machine learning tools were used to identify key features influencing citation impact. Both the papers’ external and quality information were considered in constructing papers’ feature space. Based on the feature space, the soft fuzzy rough set was used to generate a series of associated feature subsets. Then, the KNN classifier was used to find the feature subset with the best classification performance. The results show that citation impact could be predicted by objectively assessed factors. Both the papers’ quality and external features, mainly represented as the reputation of the first author, are contributed to future citation impact.

Suggested Citation

  • Mingyang Wang & Guang Yu & Shuang An & Daren Yu, 2012. "Discovery of factors influencing citation impact based on a soft fuzzy rough set model," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 635-644, December.
    • Handle: RePEc:spr:scient:v:93:y:2012:i:3:d:10.1007_s11192-012-0766-x
    DOI: 10.1007/s11192-012-0766-x
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    References listed on IDEAS

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    3. Mingyang Wang & Jiaqi Zhang & Shijia Jiao & Tianyu Zhang, 2019. "Evaluating the impact of citations of articles based on knowledge flow patterns hidden in the citations," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-19, November.
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