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The linguistic patterns and rhetorical structure of citation context: an approach using n-grams

Author

Listed:
  • Marc Bertin

    (Université du Québec à Montréal)

  • Iana Atanassova

    (Université de Bourgogne Franche-Comté)

  • Cassidy R. Sugimoto

    (Indiana University Bloomington)

  • Vincent Lariviere

    (Université de Montréal
    Université du Québec à Montréal)

Abstract

Using the full-text corpus of more than 75,000 research articles published by seven PLOS journals, this paper proposes a natural language processing approach for identifying the function of citations. Citation contexts are assigned based on the frequency of n-gram co-occurrences located near the citations. Results show that the most frequent linguistic patterns found in the citation contexts of papers vary according to their location in the IMRaD structure of scientific articles. The presence of negative citations is also dependent on this structure. This methodology offers new perspectives to locate these discursive forms according to the rhetorical structure of scientific articles, and will lead to a better understanding of the use of citations in scientific articles.

Suggested Citation

  • Marc Bertin & Iana Atanassova & Cassidy R. Sugimoto & Vincent Lariviere, 2016. "The linguistic patterns and rhetorical structure of citation context: an approach using n-grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1417-1434, December.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2134-8
    DOI: 10.1007/s11192-016-2134-8
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    References listed on IDEAS

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    Cited by:

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    2. Iman Tahamtan & Lutz Bornmann, 2019. "What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1635-1684, December.
    3. Lutz Bornmann & Alexander Tekles, 2019. "Disruptive papers published in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 331-336, July.
    4. Bowen Ma & Chengzhi Zhang & Yuzhuo Wang & Sanhong Deng, 2022. "Enhancing identification of structure function of academic articles using contextual information," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 885-925, February.
    5. Small, Henry, 2018. "Characterizing highly cited method and non-method papers using citation contexts: The role of uncertainty," Journal of Informetrics, Elsevier, vol. 12(2), pages 461-480.
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    7. Lutz Bornmann & Robin Haunschild, 2017. "Quality and impact considerations in bibliometrics: a reply to Ricker (in press)," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1857-1859, June.
    8. Shengzhi Huang & Jiajia Qian & Yong Huang & Wei Lu & Yi Bu & Jinqing Yang & Qikai Cheng, 2022. "Disclosing the relationship between citation structure and future impact of a publication," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(7), pages 1025-1042, July.
    9. Lutz Bornmann & K. Brad Wray & Robin Haunschild, 2020. "Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. K," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1051-1074, February.
    10. Martin Ricker, 2017. "Letter to the Editor: About the quality and impact of scientific articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1851-1855, June.
    11. Sergey Parinov, 2021. "Citation contexts as a data source for evaluation of scholarly consumption," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9249-9265, November.
    12. Mingyang Wang & Jiaqi Zhang & Shijia Jiao & Xiangrong Zhang & Na Zhu & Guangsheng Chen, 2020. "Important citation identification by exploiting the syntactic and contextual information of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2109-2129, December.
    13. Sven E. Hug & Martin P. Brändle, 2017. "The coverage of Microsoft Academic: analyzing the publication output of a university," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1551-1571, December.
    14. Eugenio Petrovich, 2018. "Accumulation of knowledge in para-scientific areas: the case of analytic philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1123-1151, August.
    15. Hei-Chia Wang & Jen-Wei Cheng & Che-Tsung Yang, 2022. "SentCite: a sentence-level citation recommender based on the salient similarity among multiple segments," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2521-2546, May.
    16. Bart Thijs, 2020. "Using neural-network based paragraph embeddings for the calculation of within and between document similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 835-849, November.
    17. Tahamtan, Iman & Bornmann, Lutz, 2018. "Core elements in the process of citing publications: Conceptual overview of the literature," Journal of Informetrics, Elsevier, vol. 12(1), pages 203-216.
    18. Shi, Xuanyu & Du, Jian, 2022. "Distinguishing transformative from incremental clinical evidence: A classifier of clinical research using textual features from abstracts and citing sentences," Journal of Informetrics, Elsevier, vol. 16(2).
    19. Zhiya Zuo & Kang Zhao, 2021. "Understanding and predicting future research impact at different career stages—A social network perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 454-472, April.

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