mlsanityData to 7 Oct 2026

Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications

arXiv 2212.09676 ↗First posted 19 Dec 2022cs.CL cs.DLcited by 14

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Abstract (arXiv)

Scholarly text is often laden with jargon, or specialized language that can facilitate efficient in-group communication within fields but hinder understanding for out-groups. In this work, we develop and validate an interpretable approach for measuring scholarly jargon from text. Expanding the scope of prior work which focuses on word types, we use word sense induction to also identify words that are widespread but overloaded with different meanings across fields. We then estimate the prevalence of these discipline-specific words and senses across hundreds of subfields, and show that word senses provide a complementary, yet unique view of jargon alongside word types. We demonstrate the utility of our metrics for science of science and computational sociolinguistics by highlighting two key social implications. First, though most fields reduce their use of jargon when writing for general-purpose venues, and some fields (e.g., biological sciences) do so less than others. Second, the direction of correlation between jargon and citation rates varies among fields, but jargon is nearly always negatively correlated with interdisciplinary impact. Broadly, our findings suggest that though multidisciplinary venues intend to cater to more general audiences, some fields' writing norms may act as barriers rather than bridges, and thus impede the dispersion of scholarly ideas.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 16 of its 96 references that are in the map. First posted on arXiv 19 Dec 2022.

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16 of 96 references.

References · 16

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4 more
  1. 2021Large Scale Substitution-based Word Sense Inductioncited by 9
  2. 2018Interdisciplinarity as Diversity in Citation Patterns among Journals: Rao-Stirling Diversity, Relative Variety, and the Gini coefficientcited by 7
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  4. 2022Predicting Long-Term Citations from Short-Term Linguistic Influencecited by 3

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Citing papers per year: 2023: 2; 2024: 2; 2025: 8; 2026: 2.

14 papers.

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