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Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study

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  • Paul Donner

    (German Centre for Higher Education Research and Science Studies (DZHW))

Abstract

In this study we propose and evaluate a method to automatically identify the journal publications that are related to a Ph.D. thesis using bibliographical data of both items. We build a manually curated ground truth dataset from German cumulative doctoral theses that explicitly list the included publications, which we match with records in the Scopus database. We then test supervised classification methods on the task of identifying the correct associated publications among high numbers of potential candidates using features of the thesis and publication records. The results indicate that this approach results in good match quality in general and with the best results attained by the “random forest” classification algorithm.

Suggested Citation

  • Paul Donner, 2022. "Algorithmic identification of Ph.D. thesis-related publications: a proof-of-concept study," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5863-5877, October.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:10:d:10.1007_s11192-022-04480-w
    DOI: 10.1007/s11192-022-04480-w
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    References listed on IDEAS

    as
    1. Mercedes Echeverria & David Stuart & Tobias Blanke, 2015. "Medical theses and derivative articles: dissemination of contents and publication patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 559-586, January.
    2. Paul Donner, 2021. "Citation analysis of Ph.D. theses with data from Scopus and Google Books," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9431-9456, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Cumulative dissertation; Doctoral thesis; Supervised classification; Early career researchers; Publication-based dissertation;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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