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Linguistic perspectives in deciphering citation function classification

Author

Listed:
  • Marc Bertin

    (Claude Bernard Lyon 1 University)

  • Iana Atanassova

    (Université de Franche-Comté, CRIT
    Institut Universitaire de France (IUF))

Abstract

Understanding citations within their context is a complex task in information science, critical for bibliometric analysis. The study of citation contexts and their types has been a central issue in recent work on citations. In this paper, we present an experiment on the semantic annotation of citation contexts using a rule-based approach. We processed articles from seven PLOS journals and performed semantic annotation of citation contexts based on linguistic resources we constructed. We built on previous work on verb form analysis, n-grams, and semantic category modeling in the form of a linguistic ontology. Based on our observations, we propose directions of work for the constitution of a semantically annotated corpora. The intermediate results obtained lead us to formulate hypotheses on the relation between the IMRaD structure and certain semantic categories. Furthermore, our results demonstrate the semantic richness of citation contexts and underscore the importance of access to full-text articles for ontology population in open science. The findings suggest that semantic categories vary across disciplines and rhetorical structures, necessitating further exploration with larger and more diverse datasets.

Suggested Citation

  • Marc Bertin & Iana Atanassova, 2024. "Linguistic perspectives in deciphering citation function classification," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(10), pages 6301-6313, October.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:10:d:10.1007_s11192-024-05082-4
    DOI: 10.1007/s11192-024-05082-4
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    References listed on IDEAS

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    1. Marc Bertin & Iana Atanassova & Yves Gingras & Vincent Larivière, 2016. "The invariant distribution of references in scientific articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 164-177, January.
    2. Boyack, Kevin W. & van Eck, Nees Jan & Colavizza, Giovanni & Waltman, Ludo, 2018. "Characterizing in-text citations in scientific articles: A large-scale analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 59-73.
    3. Xiaodan Zhu & Peter Turney & Daniel Lemire & André Vellino, 2015. "Measuring academic influence: Not all citations are equal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 408-427, February.
    4. Xiaozhong Liu & Jinsong Zhang & Chun Guo, 2013. "Full‐text citation analysis: A new method to enhance scholarly networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(9), pages 1852-1863, September.
    5. Siniša Maričić & Jagoda Spaventi & Leo Pavičić & Greta Pifat‐Mrzljak, 1998. "Citation context versus the frequency counts of citation histories," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(6), pages 530-540.
    6. Tarek Saier & Michael Färber, 2020. "unarXive: a large scholarly data set with publications’ full-text, annotated in-text citations, and links to metadata," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 3085-3108, December.
    7. Frederique Bordignon, 2020. "Self-correction of science: a comparative study of negative citations and post-publication peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1225-1239, August.
    8. Xiaorui Jiang & Jingqiang Chen, 2023. "Contextualised segment-wise citation function classification," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5117-5158, September.
    9. Xiaozhong Liu & Jinsong Zhang & Chun Guo, 2013. "Full-text citation analysis: A new method to enhance scholarly networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(9), pages 1852-1863, September.
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