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Data sets for author name disambiguation: an empirical analysis and a new resource

Author

Listed:
  • Mark-Christoph Müller

    (Heidelberg Institute for Theoretical Studies)

  • Florian Reitz

    (DBLP)

  • Nicolas Roy

    (FIZ Karlsruhe)

Abstract

Data sets of publication meta data with manually disambiguated author names play an important role in current author name disambiguation (AND) research. We review the most important data sets used so far, and compare their respective advantages and shortcomings. From the results of this review, we derive a set of general requirements to future AND data sets. These include both trivial requirements, like absence of errors and preservation of author order, and more substantial ones, like full disambiguation and adequate representation of publications with a small number of authors and highly variable author names. On the basis of these requirements, we create and make publicly available a new AND data set, SCAD-zbMATH. Both the quantitative analysis of this data set and the results of our initial AND experiments with a naive baseline algorithm show the SCAD-zbMATH data set to be considerably different from existing ones. We consider it a useful new resource that will challenge the state of the art in AND and benefit the AND research community.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2363-5
    DOI: 10.1007/s11192-017-2363-5
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    References listed on IDEAS

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    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. Bruno S. Frey & Katja Rost, 2010. "Do rankings reflect research quality?," Journal of Applied Economics, Universidad del CEMA, vol. 13, pages 1-38, May.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Peter Weingart, 2005. "Impact of bibliometrics upon the science system: Inadvertent consequences?," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(1), pages 117-131, January.
    8. Jinseok Kim & Jana Diesner, 2016. "Distortive effects of initial-based name disambiguation on measurements of large-scale coauthorship networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(6), pages 1446-1461, June.
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    Cited by:

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    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.
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    6. 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.
    7. Yuto Chikazawa & Marie Katsurai & Ikki Ohmukai, 2021. "Multilingual author matching across different academic databases: a case study on KAKEN, DBLP, and PubMed," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2311-2327, March.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Orzechowski, Kamil P. & Mrowinski, Maciej J. & Fronczak, Agata & Fronczak, Piotr, 2023. "Asymmetry of social interactions and its role in link predictability: The case of coauthorship networks," Journal of Informetrics, Elsevier, vol. 17(2).

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