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‘Seed + expand’: a general methodology for detecting publication oeuvres of individual researchers

Author

Listed:
  • Linda Reijnhoudt

    (Royal Netherlands Academy of Arts and Sciences (KNAW))

  • Rodrigo Costas

    (Center for Science and Technology Studies (CWTS)-Leiden University)

  • Ed Noyons

    (Center for Science and Technology Studies (CWTS)-Leiden University)

  • Katy Börner

    (Royal Netherlands Academy of Arts and Sciences (KNAW)
    Indiana University)

  • Andrea Scharnhorst

    (Royal Netherlands Academy of Arts and Sciences (KNAW))

Abstract

The study of science at the individual scholar level requires the disambiguation of author names. The creation of author’s publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed + expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980–2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify ‘seed publications’ for each author using five different approaches. Subsequently, we ‘expand’ the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a ‘gold standard’ dataset of authors for which verified publications in the period 2001–2010 are available.

Suggested Citation

  • Linda Reijnhoudt & Rodrigo Costas & Ed Noyons & Katy Börner & Andrea Scharnhorst, 2014. "‘Seed + expand’: a general methodology for detecting publication oeuvres of individual researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1403-1417, November.
    • Handle: RePEc:spr:scient:v:101:y:2014:i:2:d:10.1007_s11192-014-1256-0
    DOI: 10.1007/s11192-014-1256-0
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    References listed on IDEAS

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    2. Alexander Karlsson & Björn Hammarfelt & H. Joe Steinhauer & Göran Falkman & Nasrine Olson & Gustaf Nelhans & Jan Nolin, 2015. "Modeling uncertainty in bibliometrics and information retrieval: an information fusion approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2255-2274, March.
    3. Abdelghani Maddi & Lesya Baudoin, 2022. "The quality of the web of science data: a longitudinal study on the completeness of authors-addresses links," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6279-6292, November.
    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.

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