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Citation impact prediction for scientific papers using stepwise regression analysis

Author

Listed:
  • Tian Yu

    (Harbin Institute of Technology)

  • Guang Yu

    (Harbin Institute of Technology)

  • Peng-Yu Li

    (Harbin Institute of Technology)

  • Liang Wang

    (Harbin Institute of Technology)

Abstract

Researchers typically pay greater attention to scientific papers published within the last 2 years, and especially papers that may have great citation impact in the future. However, the accuracy of current citation impact prediction methods is still not satisfactory. This paper argues that objective features of scientific papers can make citation impact prediction relatively accurate. The external features of a paper, features of authors, features of the journal of publication, and features of citations are all considered in constructing a paper’s feature space. The stepwise multiple regression analysis is used to select appropriate features from the space and to build a regression model for explaining the relationship between citation impact and the chosen features. The validity of this model is also experimentally verified in the subject area of Information Science & Library Science. The results show that the regression model is effective within this subject.

Suggested Citation

  • Tian Yu & Guang Yu & Peng-Yu Li & Liang Wang, 2014. "Citation impact prediction for scientific papers using stepwise regression analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1233-1252, November.
    • Handle: RePEc:spr:scient:v:101:y:2014:i:2:d:10.1007_s11192-014-1279-6
    DOI: 10.1007/s11192-014-1279-6
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    References listed on IDEAS

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    1. Sei‐Ching Joanna Sin, 2011. "International coauthorship and citation impact: A bibliometric study of six LIS journals, 1980–2008," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(9), pages 1770-1783, September.
    2. Loet Leydesdorff, 2012. "Alternatives to the journal impact factor: I3 and the top-10% (or top-25%?) of the most-highly cited papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 355-365, August.
    3. Hendrik P. van Dalen & Kène Henkens, 1999. "How Influential Are Demography Journals?," Population and Development Review, The Population Council, Inc., vol. 25(2), pages 229-251, June.
    4. Quentin L. Burrell, 2003. "Predicting future citation behavior," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 372-378, March.
    5. Hendrik P. van Dalen & K?ne Henkens, 2005. "Signals in science - On the importance of signaling in gaining attention in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(2), pages 209-233, August.
    6. Rickard Danell, 2011. "Can the quality of scientific work be predicted using information on the author's track record?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(1), pages 50-60, January.
    7. Mingyang Wang & Guang Yu & Daren Yu, 2011. "Mining typical features for highly cited papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 695-706, June.
    8. Radicchi, Filippo & Castellano, Claudio, 2012. "Testing the fairness of citation indicators for comparison across scientific domains: The case of fractional citation counts," Journal of Informetrics, Elsevier, vol. 6(1), pages 121-130.
    9. Sei-Ching Joanna Sin, 2011. "International coauthorship and citation impact: A bibliometric study of six LIS journals, 1980–2008," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1770-1783, September.
    10. Loet Leydesdorff & Lutz Bornmann, 2011. "Integrated impact indicators compared with impact factors: An alternative research design with policy implications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(11), pages 2133-2146, November.
    11. 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.
    12. Lawrence D. Fu & Constantin F. Aliferis, 2010. "Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 257-270, October.
    13. Rickard Danell, 2011. "Can the quality of scientific work be predicted using information on the author's track record?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(1), pages 50-60, January.
    14. Fereshteh Didegah & Mike Thelwall, 2013. "Determinants of research citation impact in nanoscience and nanotechnology," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(5), pages 1055-1064, May.
    15. Lawrence D. Fu & Yindalon Aphinyanaphongs & Constantin F. Aliferis, 2013. "Computer models for identifying instrumental citations in the biomedical literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 871-882, December.
    16. Fereshteh Didegah & Mike Thelwall, 2013. "Determinants of research citation impact in nanoscience and nanotechnology," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(5), pages 1055-1064, May.
    17. Hendrik P. Van Dalen & Kène Henkens, 2001. "What makes a scientific article influential? The case of demographers," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(3), pages 455-482, March.
    18. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    19. Wolfgang Glänzel & Balázs Schlemmer & Bart Thijs, 2003. "Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 571-586, November.
    20. Gibbons, Michael R., 1982. "Multivariate tests of financial models : A new approach," Journal of Financial Economics, Elsevier, vol. 10(1), pages 3-27, March.
    21. Katarina Prpić, 2002. "Gender and productivity differentials in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(1), pages 27-58, September.
    22. Quentin L. Burrel, 2001. "Stochastic modelling of the first-citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(1), pages 3-12, September.
    23. Dag W Aksnes, 2003. "Characteristics of highly cited papers," Research Evaluation, Oxford University Press, vol. 12(3), pages 159-170, December.
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