IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v126y2021i3d10.1007_s11192-020-03826-6.html
   My bibliography  Save this article

ORCID-linked labeled data for evaluating author name disambiguation at scale

Author

Listed:
  • Jinseok Kim

    (University of Michigan)

  • Jason Owen-Smith

    (University of Michigan)

Abstract

How can we evaluate the performance of a disambiguation method implemented on big bibliographic data? This study suggests that the open researcher profile system, ORCID, can be used as an authority source to label name instances at scale. This study demonstrates the potential by evaluating the disambiguation performances of Author-ity2009 (which algorithmically disambiguates author names in MEDLINE) using 3 million name instances that are automatically labeled through linkage to 5 million ORCID researcher profiles. Results show that although ORCID-linked labeled data do not effectively represent the population of name instances in Author-ity2009, they do effectively capture the ‘high precision over high recall’ performances of Author-ity2009. In addition, ORCID-linked labeled data can provide nuanced details about the Author-ity2009’s performance when name instances are evaluated within and across ethnicity categories. As ORCID continues to be expanded to include more researchers, labeled data via ORCID-linkage can be improved in representing the population of a whole disambiguated data and updated on a regular basis. This can benefit author name disambiguation researchers and practitioners who need large-scale labeled data but lack resources for manual labeling or access to other authority sources for linkage-based labeling. The ORCID-linked labeled data for Author-ity2009 are publicly available for validation and reuse.

Suggested Citation

  • Jinseok Kim & Jason Owen-Smith, 2021. "ORCID-linked labeled data for evaluating author name disambiguation at scale," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2057-2083, March.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:3:d:10.1007_s11192-020-03826-6
    DOI: 10.1007/s11192-020-03826-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-020-03826-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-020-03826-6?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. Milojević, Staša, 2013. "Accuracy of simple, initials-based methods for author name disambiguation," Journal of Informetrics, Elsevier, vol. 7(4), pages 767-773.
    2. Vincent Larivière & Chaoqun Ni & Yves Gingras & Blaise Cronin & Cassidy R. Sugimoto, 2013. "Bibliometrics: Global gender disparities in science," Nature, Nature, vol. 504(7479), pages 211-213, December.
    3. Shubhanshu Mishra & Brent D Fegley & Jana Diesner & Vetle I Torvik, 2018. "Self-citation is the hallmark of productive authors, of any gender," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-21, September.
    4. Hirotaka Kawashima & Hiroyuki Tomizawa, 2015. "Accuracy evaluation of Scopus Author ID based on the largest funding database in Japan," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1061-1071, June.
    5. Ricardo G. Cota & Anderson A. Ferreira & Cristiano Nascimento & Marcos André Gonçalves & Alberto H. F. Laender, 2010. "An unsupervised heuristic-based hierarchical method for name disambiguation in bibliographic citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1853-1870, September.
    6. Wanli Liu & Rezarta Islamaj Doğan & Sun Kim & Donald C. Comeau & Won Kim & Lana Yeganova & Zhiyong Lu & W. John Wilbur, 2014. "Author name disambiguation for PubMed," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 765-781, April.
    7. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large‐scale research assessments," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    8. Jan Youtie & Stephen Carley & Alan L. Porter & Philip Shapira, 2017. "Tracking researchers and their outputs: new insights from ORCIDs," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 437-453, October.
    9. Brent D Fegley & Vetle I Torvik, 2013. "Has Large-Scale Named-Entity Network Analysis Been Resting on a Flawed Assumption?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-16, July.
    10. Dongwook Shin & Taehwan Kim & Joongmin Choi & Jungsun Kim, 2014. "Author name disambiguation using a graph model with node splitting and merging based on bibliographic information," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 15-50, July.
    11. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    12. Ricardo G. Cota & Anderson A. Ferreira & Cristiano Nascimento & Marcos André Gonçalves & Alberto H. F. Laender, 2010. "An unsupervised heuristic‐based hierarchical method for name disambiguation in bibliographic citations," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(9), pages 1853-1870, September.
    13. Jian Wang, 2013. "Citation time window choice for research impact evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 851-872, March.
    14. Michael Levin & Stefan Krawczyk & Steven Bethard & Dan Jurafsky, 2012. "Citation‐based bootstrapping for large‐scale author disambiguation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(5), pages 1030-1047, May.
    15. Jinseok Kim, 2019. "A fast and integrative algorithm for clustering performance evaluation in author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 661-681, August.
    16. Mark-Christoph Müller & Florian Reitz & Nicolas Roy, 2017. "Data sets for author name disambiguation: an empirical analysis and a new resource," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1467-1500, June.
    17. Jinseok Kim, 2019. "Scale‐free collaboration networks: An author name disambiguation perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(7), pages 685-700, July.
    18. Song, Min & Kim, Erin Hea-Jin & Kim, Ha Jin, 2015. "Exploring author name disambiguation on PubMed-scale," Journal of Informetrics, Elsevier, vol. 9(4), pages 924-941.
    19. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author-based citation analysis?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    20. Jinseok Kim & Jenna Kim, 2020. "Effect of forename string on author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 839-855, July.
    21. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    22. Jinseok Kim & Jinmo Kim & Jason Owen-Smith, 2019. "Generating automatically labeled data for author name disambiguation: an iterative clustering method," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 253-280, January.
    23. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author‐based citation analysis?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    24. Alan Filipe Santana & Marcos André Gonçalves & Alberto H. F. Laender & Anderson A. Ferreira, 2017. "Incremental author name disambiguation by exploiting domain-specific heuristics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 931-945, April.
    25. Jinseok Kim, 2018. "Evaluating author name disambiguation for digital libraries: a case of DBLP," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1867-1886, September.
    26. Janaína Gomide & Hugo Kling & Daniel Figueiredo, 2017. "Name usage pattern in the synonym ambiguity problem in bibliographic data," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 747-766, August.
    27. Michael Levin & Stefan Krawczyk & Steven Bethard & Dan Jurafsky, 2012. "Citation-based bootstrapping for large-scale author disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(5), pages 1030-1047, May.
    28. Vetle I. Torvik & Marc Weeber & Don R. Swanson & Neil R. Smalheiser, 2005. "A probabilistic similarity metric for Medline records: A model for author name disambiguation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(2), pages 140-158, January.
    29. 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.
    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. Jaime A. Teixeira da Silva, 2021. "Abuse of ORCID’s weaknesses by authors who use paper mills," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6119-6125, July.
    2. Li Zhang & Wei Lu & Jinqing Yang, 2023. "LAGOS‐AND: A large gold standard dataset for scholarly author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(2), pages 168-185, February.
    3. Humaira Waqas & Abdul Qadir, 2022. "Completing features for author name disambiguation (AND): an empirical analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 1039-1063, February.
    4. Brito, Ana C.M. & Silva, Filipi N. & Amancio, Diego R., 2021. "Associations between author-level metrics in subsequent time periods," Journal of Informetrics, Elsevier, vol. 15(4).
    5. Jinseok Kim & Jenna Kim & Jason Owen‐Smith, 2021. "Ethnicity‐based name partitioning for author name disambiguation using supervised machine learning," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(8), pages 979-994, August.

    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. Jinseok Kim & Jinmo Kim & Jason Owen-Smith, 2019. "Generating automatically labeled data for author name disambiguation: an iterative clustering method," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 253-280, January.
    2. Ciriaco Andrea D’Angelo & Nees Jan Eck, 2020. "Collecting large-scale publication data at the level of individual researchers: a practical proposal for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 883-907, May.
    3. Jinseok Kim, 2019. "A fast and integrative algorithm for clustering performance evaluation in author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 661-681, August.
    4. Jinseok Kim, 2018. "Evaluating author name disambiguation for digital libraries: a case of DBLP," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1867-1886, September.
    5. Jinseok Kim & Jenna Kim & Jason Owen‐Smith, 2021. "Ethnicity‐based name partitioning for author name disambiguation using supervised machine learning," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(8), pages 979-994, August.
    6. Jinseok Kim & Jenna Kim, 2020. "Effect of forename string on author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 839-855, July.
    7. Jan Schulz, 2016. "Using Monte Carlo simulations to assess the impact of author name disambiguation quality on different bibliometric analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1283-1298, June.
    8. Humaira Waqas & Abdul Qadir, 2022. "Completing features for author name disambiguation (AND): an empirical analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 1039-1063, February.
    9. Li Zhang & Wei Lu & Jinqing Yang, 2023. "LAGOS‐AND: A large gold standard dataset for scholarly author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(2), pages 168-185, February.
    10. Humaira Waqas & Muhammad Abdul Qadir, 2021. "Multilayer heuristics based clustering framework (MHCF) for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7637-7678, September.
    11. Shuiqing Huang & Bo Yang & Sulan Yan & Ronald Rousseau, 2014. "Institution name disambiguation for research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 823-838, June.
    12. Kim, Jinseok & Diesner, Jana, 2015. "The effect of data pre-processing on understanding the evolution of collaboration networks," Journal of Informetrics, Elsevier, vol. 9(1), pages 226-236.
    13. Jinseok Kim & Jenna Kim, 2018. "The impact of imbalanced training data on machine learning for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 511-526, October.
    14. Helena Mihaljević & Lucía Santamaría, 2021. "Disambiguation of author entities in ADS using supervised learning and graph theory methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3893-3917, May.
    15. KM. Pooja & Samrat Mondal & Joydeep Chandra, 2021. "Exploiting similarities across multiple dimensions for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7525-7560, September.
    16. Hao Wu & Bo Li & Yijian Pei & Jun He, 2014. "Unsupervised author disambiguation using Dempster–Shafer theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1955-1972, December.
    17. Song, Min & Kim, Erin Hea-Jin & Kim, Ha Jin, 2015. "Exploring author name disambiguation on PubMed-scale," Journal of Informetrics, Elsevier, vol. 9(4), pages 924-941.
    18. Milojević, Staša, 2013. "Accuracy of simple, initials-based methods for author name disambiguation," Journal of Informetrics, Elsevier, vol. 7(4), pages 767-773.
    19. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    20. Abramo, Giovanni & D'Angelo, Ciriaco Andrea & Grilli, Leonardo, 2021. "The effects of citation-based research evaluation schemes on self-citation behavior," Journal of Informetrics, Elsevier, vol. 15(4).

    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:spr:scient:v:126:y:2021:i:3:d:10.1007_s11192-020-03826-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.