Detecting and analyzing missing citations to published scientific entities
Jialiang Lin, Yao Yu, Jiaxin Song, Xiaodong Shi

TL;DR
This paper introduces a method called CRPSE to recommend citations for scientific entities that are often under-cited, and analyzes the prevalence of missing citations in recent computer science conference papers.
Contribution
The paper presents a novel citation recommendation method based on co-occurrences and provides a statistical analysis of missing citations in high-impact computer science publications.
Findings
CRPSE effectively recommends source papers for scientific entities.
Approximately 3.9% of entities in 2020 papers had missing citations.
Many well-accepted research results are often cited without proper attribution.
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…
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