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Collecting large-scale publication data at the level of individual researchers: a practical proposal for author name disambiguation

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Abstract

The disambiguation of author names is an important and challenging task in bibliometrics. We propose an approach that relies on an external source of information for selecting and validating clusters of publications identified through an unsupervised author name disambiguation method. The application of the proposed approach to a random sample of Italian scholars shows encouraging results, with an overall precision, recall, and F-measure of over 96%. The proposed approach can serve as a starting point for large-scale census of publication portfolios for bibliometric analyses at the level of individual researchers.

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Notes

  1. http://cercauniversita.cineca.it/php5/docenti/cerca.php, last accessed 20/09/2019.

  2. The complete list is accessible at attiministeriali.miur.it/userfiles/115.htm, last accessed 20/09/2019.

  3. Note that this filtering stage differs from that in the original DGA method: in the original DGA method, author-identity pairs are filtered; in the proposed approach, complete clusters are filtered.

  4. The percent sign (%) wildcard allows to retrieve any name starting with the text preceding the sign.

  5. In fact, these publications are also ignored by the DGA algorithm, which is applied only to articles indexed in the Italian National Citation Report.

  6. The reader may wonder why a “manual validation” is performed in an approach proposed for “large scale” author name disambiguation. As we will see better below, this scenario is presented only to understand the trade-off between costs and benefits of this scenario and the less costly alternative scenarios in which no manual validation is involved.

  7. All Italian university research staff hold an ORCID identifier, following the IRIDE project launched in 2014 by the MIUR.

  8. We have excluded documents published in a year in which the relevant author was not a tenured professor in the Italian academic system.

  9. Baseline 1 is a simple method often performed by scholars in practice. Given the high share of potential homonyms (29% as shown in Table 5), we expect a low level of precision when applying such method. Baseline 2 should solve most homonym cases but could lead to a low level of recall due to an increasing number of false negatives.

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Authors and Affiliations

  1. Department of Engineering and Management, University of Rome “Tor Vergata”, Rome, Italy

    Ciriaco Andrea D’Angelo

  2. Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands

    Nees Jan van Eck

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  1. Ciriaco Andrea D’Angelo
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  2. Nees Jan van Eck
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Correspondence to Ciriaco Andrea D’Angelo.

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D’Angelo, C.A., van Eck, N.J. Collecting large-scale publication data at the level of individual researchers: a practical proposal for author name disambiguation. Scientometrics 123, 883–907 (2020). https://doi.org/10.1007/s11192-020-03410-y

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