IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v15y2021i1s1751157720306222.html
   My bibliography  Save this article

Mitigating ageing bias in article level metrics using citation network analysis

Author

Listed:
  • Tóth, István
  • Lázár, Zsolt I.
  • Varga, Levente
  • Járai-Szabó, Ferenc
  • Papp, István
  • Florian, Răzvan V.
  • Ercsey-Ravasz, Mária

Abstract

Article level scientometric indicators (ALMs) are usually of cumulative nature making articles of different age hard to compare. Here, we introduce a new ALM, the Time Debiased Significance Score (TDSS), which measures the significance of a publication based on the structure of the whole citation network and eliminates the global ageing bias in the network: older publications should not be a priori privileged or disadvantaged compared to newer ones. The TDSS is based on a modified variant of the PageRank measure, incorporating a mathematically consistent temporal detrending and ensuring a few key features: (i) the TDSS should not show any global trend as a function of the topological index (causal order in the citation network); (ii) the TDSS value of a publication should decrease as time passes (and the citation network grows) if no more citations are associated with it. The above definition is beneficial in multiple ways, including e.g. low computational complexity and weak domain dependence. Further, estimation of reliability of the TDSS and its extension to groups of items like overall score of a research group are also possible.

Suggested Citation

  • Tóth, István & Lázár, Zsolt I. & Varga, Levente & Járai-Szabó, Ferenc & Papp, István & Florian, Răzvan V. & Ercsey-Ravasz, Mária, 2021. "Mitigating ageing bias in article level metrics using citation network analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    • Handle: RePEc:eee:infome:v:15:y:2021:i:1:s1751157720306222
    DOI: 10.1016/j.joi.2020.101105
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157720306222
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2020.101105?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. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    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. Kalervo Järvelin & Olle Persson, 2008. "Erratum re: “The DCI‐index: Discounted cumulated impact‐based research evaluation”, Journal of the American Society for Information Science and Technology, 59(9), 1433‐1440," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(14), pages 2350-2352, December.
    4. Kalervo Järvelin & Olle Persson, 2008. "The DCI index: Discounted cumulated impact‐based research evaluation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(9), pages 1433-1440, July.
    5. Dalibor Fiala, 2014. "Current index: A Proposal for a dynamic rating system for researchers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 850-855, April.
    6. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    7. Zoltán Néda & Levente Varga & Tamás S Biró, 2017. "Science and Facebook: The same popularity law!," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-11, July.
    8. Anthony F. J. van Raan, 2004. "Sleeping Beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 467-472, March.
    9. Parolo, Pietro Della Briotta & Pan, Raj Kumar & Ghosh, Rumi & Huberman, Bernardo A. & Kaski, Kimmo & Fortunato, Santo, 2015. "Attention decay in science," Journal of Informetrics, Elsevier, vol. 9(4), pages 734-745.
    10. Young-Ho Eom & Santo Fortunato, 2011. "Characterizing and Modeling Citation Dynamics," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-7, September.
    11. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    12. Michel Zitt & Henry Small, 2008. "Modifying the journal impact factor by fractional citation weighting: The audience factor," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(11), pages 1856-1860, September.
    13. Ludo Waltman & Nees Jan Eck, 2013. "Source normalized indicators of citation impact: an overview of different approaches and an empirical comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 699-716, September.
    14. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu, Shuo & Alqahtani, Fayez & Tolba, Amr & Lee, Ivan & Jia, Tao & Xia, Feng, 2022. "Collaborative Team Recognition: A Core Plus Extension Structure," Journal of Informetrics, Elsevier, vol. 16(4).
    2. Arturas Kaklauskas & Edmundas Kazimieras Zavadskas & Natalija Lepkova & Saulius Raslanas & Kestutis Dauksys & Ingrida Vetloviene & Ieva Ubarte, 2021. "Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field," Sustainability, MDPI, vol. 13(13), pages 1-42, July.
    3. Regina Negri Pagani & Bruno Pedroso & Celso Bilynkievycz Santos & Claudia Tania Picinin & João Luiz Kovaleski, 2023. "Methodi Ordinatio 2.0: revisited under statistical estimation, and presenting FInder and RankIn," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4563-4602, October.

    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. Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    3. Yin, Yian & Wang, Dashun, 2017. "The time dimension of science: Connecting the past to the future," Journal of Informetrics, Elsevier, vol. 11(2), pages 608-621.
    4. 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).
    5. Kehan Wang & Wenxuan Shi & Junsong Bai & Xiaoping Zhao & Liying Zhang, 2021. "Prediction and application of article potential citations based on nonlinear citation-forecasting combined model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6533-6550, August.
    6. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    7. Liwei Cai & Jiahao Tian & Jiaying Liu & Xiaomei Bai & Ivan Lee & Xiangjie Kong & Feng Xia, 2019. "Scholarly impact assessment: a survey of citation weighting solutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 453-478, February.
    8. Akella, Akhil Pandey & Alhoori, Hamed & Kondamudi, Pavan Ravikanth & Freeman, Cole & Zhou, Haiming, 2021. "Early indicators of scientific impact: Predicting citations with altmetrics," Journal of Informetrics, Elsevier, vol. 15(2).
    9. Cena, Anna & Gagolewski, Marek & Siudem, Grzegorz & Żogała-Siudem, Barbara, 2022. "Validating citation models by proxy indices," Journal of Informetrics, Elsevier, vol. 16(2).
    10. Lutz Bornmann & Alexander Tekles & Loet Leydesdorff, 2019. "How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1187-1205, May.
    11. Tolga Yuret, 2018. "Author-weighted impact factor and reference return ratio: can we attain more equality among fields?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2097-2111, September.
    12. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    13. Zhou, Ping & Leydesdorff, Loet, 2011. "Fractional counting of citations in research evaluation: A cross- and interdisciplinary assessment of the Tsinghua University in Beijing," Journal of Informetrics, Elsevier, vol. 5(3), pages 360-368.
    14. Elizabeth S. Vieira, 2023. "The influence of research collaboration on citation impact: the countries in the European Innovation Scoreboard," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3555-3579, June.
    15. Nadia Simoes & Nuno Crespo, 2020. "A flexible approach for measuring author-level publishing performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 331-355, January.
    16. 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.
    17. Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.
    18. Yuanyuan Liu & Qiang Wu & Shijie Wu & Yong Gao, 2021. "Weighted citation based on ranking-related contribution: a new index for evaluating article impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8653-8672, October.
    19. Chao Lu & Ying Ding & Chengzhi Zhang, 2017. "Understanding the impact change of a highly cited article: a content-based citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 927-945, August.
    20. Danielle H. Lee, 2019. "Predicting the research performance of early career scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1481-1504, December.

    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:15:y:2021:i:1:s1751157720306222. 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.