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Do Scopus and WoS correct “old” omitted citations?

Author

Listed:
  • Fiorenzo Franceschini

    (Politecnico di Torino)

  • Domenico Maisano

    (Politecnico di Torino)

  • Luca Mastrogiacomo

    (Politecnico di Torino)

Abstract

Omitted citations—i.e., missing links between a cited paper and the corresponding citing papers—are a consequence of several bibliometric-database errors. To reduce these errors, databases may undertake two actions: (1) improving the control of the (new) papers to be indexed, i.e., limiting the introduction of “new” dirty data, and (2) detecting and correcting errors in the papers already indexed by the database, i.e., cleaning “old” dirty data. The latter action is probably more complicated, as it requires the application of suitable error-detection procedures to a huge amount of data. Based on an extensive sample of scientific papers in the Engineering-Manufacturing field, this study focuses on old dirty data in the Scopus and WoS databases. To this purpose, a recent automated algorithm for estimating the omitted-citation rate of databases is applied to the same sample of papers, but in three different-time sessions. A database’s ability to clean the old dirty data is evaluated considering the variations in the omitted-citation rate from session to session. The major outcomes of this study are that: (1) both databases slowly correct old omitted citations, and (2) a small portion of initially corrected citations can surprisingly come off from databases over time.

Suggested Citation

  • Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2016. "Do Scopus and WoS correct “old” omitted citations?," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 321-335, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1867-8
    DOI: 10.1007/s11192-016-1867-8
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    References listed on IDEAS

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    1. Franceschini, Fiorenzo & Maisano, Domenico & Mastrogiacomo, Luca, 2014. "Scientific journal publishers and omitted citations in bibliometric databases: Any relationship?," Journal of Informetrics, Elsevier, vol. 8(3), pages 751-765.
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    3. Marlies Olensky & Marion Schmidt & Nees Jan Eck, 2016. "Evaluation of the citation matching algorithms of CWTS and iFQ in comparison to the Web of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(10), pages 2550-2564, October.
    4. Valderrama-Zurián, Juan-Carlos & Aguilar-Moya, Remedios & Melero-Fuentes, David & Aleixandre-Benavent, Rafael, 2015. "A systematic analysis of duplicate records in Scopus," Journal of Informetrics, Elsevier, vol. 9(3), pages 570-576.
    5. Franceschini, Fiorenzo & Maisano, Domenico & Mastrogiacomo, Luca, 2016. "The museum of errors/horrors in Scopus," Journal of Informetrics, Elsevier, vol. 10(1), pages 174-182.
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    Cited by:

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    3. Franceschini, Fiorenzo & Maisano, Domenico & Mastrogiacomo, Luca, 2016. "Empirical analysis and classification of database errors in Scopus and Web of Science," Journal of Informetrics, Elsevier, vol. 10(4), pages 933-953.
    4. Houqiang Yu & Xueting Cao & Tingting Xiao & Zhenyi Yang, 2020. "How accurate are policy document mentions? A first look at the role of altmetrics database," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1517-1540, November.
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