IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v13y2019i1p32-49.html
   My bibliography  Save this article

Predicting publication long-term impact through a combination of early citations and journal impact factor

Author

Listed:
  • Abramo, Giovanni
  • D’Angelo, Ciriaco Andrea
  • Felici, Giovanni

Abstract

The ability to predict the long-term impact of a scientific article soon after its publication is of great value towards accurate assessment of research performance. In this work we test the hypothesis that good predictions of long-term citation counts can be obtained through a combination of a publication's early citations and the impact factor of the hosting journal. The test is performed on a corpus of 123,128 WoS publications authored by Italian scientists, using linear regression models. The average accuracy of the prediction is good for citation time windows above two years, decreases for lowly-cited publications, and varies across disciplines. As expected, the role of the impact factor in the combination becomes negligible after only two years from publication.

Suggested Citation

  • Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Felici, Giovanni, 2019. "Predicting publication long-term impact through a combination of early citations and journal impact factor," Journal of Informetrics, Elsevier, vol. 13(1), pages 32-49.
  • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:32-49
    DOI: 10.1016/j.joi.2018.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157718300208
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joi.2018.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    2. Stegehuis, Clara & Litvak, Nelly & Waltman, Ludo, 2015. "Predicting the long-term citation impact of recent publications," Journal of Informetrics, Elsevier, vol. 9(3), pages 642-657.
    3. Michael J Stringer & Marta Sales-Pardo & Luís A Nunes Amaral, 2008. "Effectiveness of Journal Ranking Schemes as a Tool for Locating Information," PLOS ONE, Public Library of Science, vol. 3(2), pages 1-8, February.
    4. Mike Thelwall & Pardeep Sud, 2016. "Mendeley readership counts: An investigation of temporal and disciplinary differences," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(12), pages 3036-3050, December.
    5. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2016. "Refrain from adopting the combination of citation and journal metrics to grade publications, as used in the Italian national research assessment exercise (VQR 2011–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2053-2065, December.
    6. Stephan B. Bruns & David I. Stern, 2016. "Research assessment using early citation information," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 917-935, August.
    7. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    8. Xuemei Li & Mike Thelwall & Dean Giustini, 2012. "Validating online reference managers for scholarly impact measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 461-471, May.
    9. Pardeep Sud & Mike Thelwall, 2014. "Evaluating altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1131-1143, February.
    10. Jonathan Adams, 2005. "Early citation counts correlate with accumulated impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(3), pages 567-581, June.
    11. J Mingers, 2008. "Exploring the dynamics of journal citations: Modelling with s-curves," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1013-1025, August.
    12. Jian Wang, 2013. "Citation time window choice for research impact evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 851-872, March.
    13. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "Revisiting the scaling of citations for research assessment," Journal of Informetrics, Elsevier, vol. 6(4), pages 470-479.
    14. 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.
    15. David I Stern, 2014. "High-Ranked Social Science Journal Articles Can Be Identified from Early Citation Information," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-11, November.
    16. Susanne E. Baumgartner & Loet Leydesdorff, 2014. "Group-based trajectory modeling (GBTM) of citations in scholarly literature: Dynamic qualities of “transient” and “sticky knowledge claims”," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 797-811, April.
    17. Hadas Shema & Judit Bar-Ilan & Mike Thelwall, 2014. "Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1018-1027, May.
    18. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2010. "Citations versus journal impact factor as proxy of quality: could the latter ever be preferable?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 821-833, September.
    19. Abramo, Giovanni, 2018. "Revisiting the scientometric conceptualization of impact and its measurement," Journal of Informetrics, Elsevier, vol. 12(3), pages 590-597.
    20. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "Assessing the varying level of impact measurement accuracy as a function of the citation window length," Journal of Informetrics, Elsevier, vol. 5(4), pages 659-667.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abramo, Giovanni, 2018. "Revisiting the scientometric conceptualization of impact and its measurement," Journal of Informetrics, Elsevier, vol. 12(3), pages 590-597.
    2. Thelwall, Mike & Nevill, Tamara, 2018. "Could scientists use Altmetric.com scores to predict longer term citation counts?," Journal of Informetrics, Elsevier, vol. 12(1), pages 237-248.
    3. Wang, Xing & Zhang, Zhihui, 2020. "Improving the reliability of short-term citation impact indicators by taking into account the correlation between short- and long-term citation impact," Journal of Informetrics, Elsevier, vol. 14(2).
    4. Guoliang Lyu & Ganwei Shi, 2019. "On an approach to boosting a journal’s citation potential," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1387-1409, September.
    5. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    6. David L. Anderson & John Tressler, 2016. "Citation-Capture Rates for Economics Journals: Do they Differ from Other Disciplines and Does it Matter?," Economic Papers, The Economic Society of Australia, vol. 35(1), pages 73-85, March.
    7. Kousha, Kayvan & Thelwall, Mike & Abdoli, Mahshid, 2018. "Can Microsoft Academic assess the early citation impact of in-press articles? A multi-discipline exploratory analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 287-298.
    8. Vasilios D. Kosteas, 2018. "Predicting long-run citation counts for articles in top economics journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1395-1412, June.
    9. David I Stern, 2014. "High-Ranked Social Science Journal Articles Can Be Identified from Early Citation Information," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-11, November.
    10. Mike Thelwall, 2018. "Early Mendeley readers correlate with later citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1231-1240, June.
    11. Fairclough, Ruth & Thelwall, Mike, 2015. "National research impact indicators from Mendeley readers," Journal of Informetrics, Elsevier, vol. 9(4), pages 845-859.
    12. Andrea Fronzetti Colladon & Ciriaco Andrea D’Angelo & Peter A. Gloor, 2020. "Predicting the future success of scientific publications through social network and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 357-377, July.
    13. Stegehuis, Clara & Litvak, Nelly & Waltman, Ludo, 2015. "Predicting the long-term citation impact of recent publications," Journal of Informetrics, Elsevier, vol. 9(3), pages 642-657.
    14. Schreiber, Michael, 2015. "Restricting the h-index to a publication and citation time window: A case study of a timed Hirsch index," Journal of Informetrics, Elsevier, vol. 9(1), pages 150-155.
    15. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2021. "A bibliometric methodology to unveil territorial inequities in the scientific wealth to combat COVID-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6601-6624, August.
    16. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    17. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
    18. Cao, Xuanyu & Chen, Yan & Ray Liu, K.J., 2016. "A data analytic approach to quantifying scientific impact," Journal of Informetrics, Elsevier, vol. 10(2), pages 471-484.
    19. Marcel Clermont & Johanna Krolak & Dirk Tunger, 2021. "Does the citation period have any effect on the informative value of selected citation indicators in research evaluations?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1019-1047, February.
    20. Abramo, Giovanni & Aksnes, Dag W. & D’Angelo, Ciriaco Andrea, 2020. "Comparison of research performance of Italian and Norwegian professors and universities," Journal of Informetrics, Elsevier, vol. 14(2).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:13:y:2019:i:1:p:32-49. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.