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Detecting and analyzing missing citations to published scientific entities

Author

Listed:
  • Jialiang Lin

    (Xiamen University)

  • Yao Yu

    (Xiamen University)

  • Jiaxin Song

    (Xiamen University)

  • Xiaodong Shi

    (Xiamen University)

Abstract

Proper citation is of great importance in academic writing for it enables knowledge accumulation and maintains academic integrity. However, citing properly is not an easy task. For published scientific entities, the ever-growing academic publications and over-familiarity of terms easily lead to missing citations. To deal with this situation, we design a special method Citation Recommendation for Published Scientific Entity (CRPSE) based on the cooccurrences between published scientific entities and in-text citations in the same sentences from previous researchers. Experimental outcomes show the effectiveness of our method in recommending the source papers for published scientific entities. We further conduct a statistical analysis on missing citations among papers published in prestigious computer science conferences in 2020. In the 12,278 papers collected, 475 published scientific entities of computer science and mathematics are found to have missing citations. Many entities mentioned without citations are found to be well-accepted research results. On a median basis, the papers proposing these published scientific entities with missing citations were published 8 years ago, which can be considered the time frame for a published scientific entity to develop into a well-accepted concept. For published scientific entities, we appeal for accurate and full citation of their source papers as required by academic standards.

Suggested Citation

  • Jialiang Lin & Yao Yu & Jiaxin Song & Xiaodong Shi, 2022. "Detecting and analyzing missing citations to published scientific entities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2395-2412, May.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:5:d:10.1007_s11192-022-04334-5
    DOI: 10.1007/s11192-022-04334-5
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    References listed on IDEAS

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    Cited by:

    1. Peng, Wen & Yue, Mingliang & Sun, Mingyue & Ma, Tingcan, 2024. "Revision and academic impact: A case study of bioRxiv preprint papers," Journal of Informetrics, Elsevier, vol. 18(1).

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