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Tracing the Retraction Cascade: Identifying Non-retracted but Potentially Retractable Articles

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Linking Theory and Practice of Digital Libraries (TPDL 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 15177))

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Abstract

Scientific advancement is driven by new discoveries that often build upon previous knowledge - usually in good faith. Yet recently, there is an increasing number of either erroneous publications or even cases of scientific misconduct, as evidenced by rapidly growing numbers of retracted articles. Unfortunately, the problem is not only limited to retracted articles, but also with all articles citing them. Whenever an article is retracted, it raises concerns about the validity of its findings, rendering it an unreliable source for subsequent citations. Consequently, all articles citing a retracted article come under scrutiny. However, Re-evaluating all citing articles is a tedious, unrealistic, and unnecessary process because not all citations hold equal significance. Therefore, we aim to identify citation patterns that lead to cascading retractions. We investigate around 5000 articles citing retracted articles, including 953 cases of cascading retractions. Moreover, we propose a retraction-centric approach to rank articles that are close to retraction by measuring their similarities to bibliographically coupled retracted articles. This study presents an alternative to exhaustive re-examination, offering a more efficient means to scrutinize the articles that require re-evaluation.

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Notes

  1. 1.

    http://www.sparontologies.net/ontologies/c4o.

  2. 2.

    http://www.sparontologies.net/ontologies/fabio.

  3. 3.

    http://www.sparontologies.net/ontologies/cito.

  4. 4.

    https://pypi.org/project/beautifulsoup4/.

  5. 5.

    https://github.com/TPDL24/RetractionCascade.

  6. 6.

    The articles listed in Table 3 are identified based on textual similarity and citation analysis. This does not imply any subjective review of the content or validity of the articles. The authors do not claim that the listed articles are definitively flawed. Instead, this analysis aims to highlight potential areas for further investigation.

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Acknowledgments

This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant No. Gepris 267140244 for the PubPharm - Specialized Information Service for Pharmacy.

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Authors and Affiliations

  1. Institute for Information Systems, TU Braunschweig, Braunschweig, Germany

    Muhammad Usman & Wolf-Tilo Balke

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  1. Muhammad Usman
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Correspondence to Muhammad Usman .

Editor information

Editors and Affiliations

  1. University of Salford, Salford, UK

    Apostolos Antonacopoulos

  2. University of Waikato, Hamilton, New Zealand

    Annika Hinze

  3. Sorbonne University (CNRS), Paris, France

    Benjamin Piwowarski

  4. University of La Rochelle (L3i Laboratory), La Rochelle, France

    Mickaël Coustaty

  5. University of Padova, Padua, Italy

    Giorgio Maria Di Nunzio

  6. University of Hamburg, Hamburg, Germany

    Francesco Gelati

  7. University of Waikato, Hamilton, New Zealand

    Nicholas Vanderschantz

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Usman, M., Balke, WT. (2024). Tracing the Retraction Cascade: Identifying Non-retracted but Potentially Retractable Articles. In: Antonacopoulos, A., et al. Linking Theory and Practice of Digital Libraries. TPDL 2024. Lecture Notes in Computer Science, vol 15177. Springer, Cham. https://doi.org/10.1007/978-3-031-72437-4_7

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