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An analysis of citation functions in the humanities and social sciences research from the perspective of problematic citation analysis assumptions

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  • Chi-Shiou Lin

    (National Taiwan University
    National Taiwan University)

Abstract

Citation analyses are based on two questionable assumptions that significantly influence the value of citation count: the equal contribution assumption (i.e., each citation contributes equally to the citing paper) and the positive endorsement assumption (i.e., each citation is viewed as an endorsement from the citing paper to the cited work). This study employed a citation context analysis approach to examine the distributions of essential versus perfunctory citations as well as confirmative versus negational citations in humanities and social sciences (H&SS) research articles to determine to what extent the two problematic assumptions affect the validity of citation analyses in those fields. The sample comprises 360 articles representing six subject areas: Chinese literature, history, arts (i.e., the humanities subjects); sociology, economics, and psychology (i.e., the social sciences subjects). Excluding citations to primary sources—e.g., manuscripts, archival materials, monographs that were the subjects of study rather than information sources, a total of 25,617 in-text bibliographic citations were analyzed. The findings show that the distributions of citation functions for those six subject fields were all significantly different, meaning that disciplinary differences exist in H&SS citations. Also, for the H&SS fields, perfunctory citations may have inflated the contribution of the cited works much more than negational citations.

Suggested Citation

  • Chi-Shiou Lin, 2018. "An analysis of citation functions in the humanities and social sciences research from the perspective of problematic citation analysis assumptions," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 797-813, August.
  • Handle: RePEc:spr:scient:v:116:y:2018:i:2:d:10.1007_s11192-018-2770-2
    DOI: 10.1007/s11192-018-2770-2
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    Cited by:

    1. 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.
    2. Frederique Bordignon, 2022. "Critical citations in knowledge construction and citation analysis: from paradox to definition," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 959-972, February.
    3. Dongqing Lyu & Xuanmin Ruan & Juan Xie & Ying Cheng, 2021. "The classification of citing motivations: a meta-synthesis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3243-3264, April.
    4. Kai Nishikawa, 2023. "How and why are citations between disciplines made? A citation context analysis focusing on natural sciences and social sciences and humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2975-2997, May.
    5. Indra Budi & Yaniasih Yaniasih, 2023. "Understanding the meanings of citations using sentiment, role, and citation function classifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 735-759, January.
    6. Mike Thelwall, 2019. "Are classic references cited first? An analysis of citation order within article sections," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 723-731, August.
    7. Heng Huang & Donghua Zhu & Xuefeng Wang, 2022. "Evaluating scientific impact of publications: combining citation polarity and purpose," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5257-5281, September.
    8. Wei‐Ning Cheng & Christopher S. G. Khoo, 2021. "Information structures in sociology research papers: Modeling cause–effect and comparison relations in research objective and result statements," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(11), pages 1367-1385, November.

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