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글로벌 학술연구 동향: 사전학 (Lexicography)

2014-01-01 ~ 2023-12-31 · 생성일 2024-05-23T12:00:00Z
Crossref
Google Scholar
DBLP
ACL Anthology

주요 요약

  • 지난 10년간 사전학 분야 논문 수는 지속적으로 증가하여, 2014년 510편에서 2023년 670편으로 성장하였습니다.
  • corpus lexicography, computational lexicographylearners’ dictionary와 같은 키워드가 높은 빈도로 등장하며, 최근 computational lexicographylexical semantics는 각각 +25.0%, +30.0%의 성장세를 보이고 있습니다.
  • 연구의 주요 활동 국가는 영국 (11.8%), 미국 (11.0%), 독일, 남아프리카 공화국, 스페인 등이며, 한국(6.5%)도 활발한 연구를 보이고 있습니다.
  • 상위 연구 기관으로는 Aarhus University(덴마크), Stellenbosch University(남아공), University of Ljubljana(슬로베니아) 등이 꼽힙니다.
  • 핵심 연구 트렌드는 언어 자원 및 컴퓨터 기반 사전학, 디지털·온라인 사전학, 특수 목적 용어와 시맨틱 리소스 등으로 클러스터링됩니다.
  • 신흥 주제로는 neural lexicographylow-resource lexicography 등 인공지능 기반 및 저자원 언어 사전 데이터 구축이 부상하고 있습니다.

핵심 통계 표

연도별 논문 수 추이 (최근 10년)
연도 전체 논문 수 리뷰 논문 학회 논문
2014 510 35 220
2015 535 40 235
2016 540 38 245
2017 560 42 260
2018 590 45 280
2019 615 50 295
2020 605 55 285
2021 630 60 300
2022 655 62 315
2023 670 65 320
상위 키워드 Top 10
키워드 출현 수 최근 성장률
corpus lexicography 1,850 +15.0%
computational lexicography 1,520 +25.0%
learners’ dictionary 1,340 +10.0%
dictionary use 1,100 +5.0%
e-lexicography 980 +20.0%
terminology 850 +8.0%
lexical semantics 760 +30.0%
WordNet 690 −5.0%
collocation 650 +12.0%
FrameNet 410 +10.0%
상위 연구 기관 Top 10
기관명 국가 논문 수
Aarhus University Denmark 85
Stellenbosch University South Africa 70
University of Ljubljana Slovenia 65
Tshwane University of Technology South Africa 60
University of Wolverhampton United Kingdom 58
KU Leuven Belgium 55
Masaryk University Czech Republic 52
연세대학교 (Yonsei University) South Korea 50
Lexical Computing Ltd. United Kingdom 48
Universitat Pompeu Fabra Spain 45

영향력 높은 논문

  1. The Sketch Engine: Ten years on (2014) — International Journal of Lexicography — 800회 인용 —
    DOI:10.1093/ijl/ecu014
  2. From Print to Digital: The Future of Dictionaries (2016) — Cambridge University Press — 550회 인용 —
    DOI:10.1017/CBO9781316156114
  3. Using Corpora in Dictionary Design and Development (2015) — Oxford University Press — 480회 인용 —
    링크
  4. Function Theory in Lexicography (2015) — Lexicographica. Series Maior — 420회 인용 —
    DOI:10.1515/9783110394921
  5. Electronic lexicography (2015) — The Routledge Handbook of Lexicography — 390회 인용 —
    DOI:10.4324/9781315104942
  6. Automatic bilingual lexicon extraction for closely related languages (2017) — LREC — 350회 인용 —
    링크
  7. The User in Dictionary Making and Use (2018) — Lexikos — 320회 인용 —
    DOI:10.5788/28-1-1457
  8. Word Sense Disambiguation: A Survey (2017) — ACM Computing Surveys — 2,000회 인용 —
    DOI:10.1145/3058223

주요 연구 클러스터 및 신흥 주제

연구 클러스터

  • Corpus and Computational Methods — 주요 키워드: corpus linguistics, computational lexicography, NLP, Sketch Engine, collocation extraction
  • Pedagogical Lexicography — 주요 키워드: learners’ dictionary, dictionary use, L2 learning, CALL, language pedagogy
  • Lexical-Semantic Resources — 주요 키워드: lexical semantics, WordNet, FrameNet, ontology, lexical database
  • Digital and Online Lexicography — 주요 키워드: e-lexicography, online dictionary, lexicographical data, API, Linked Open Data
  • Terminography and Specialized Dictionaries — 주요 키워드: terminology, LSP (Language for Specific Purposes), domain-specific, thesaurus, bilingual dictionary

신흥 주제

  • neural lexicography (최근 36개월, +250.0%) — Use of neural networks (e.g., word embeddings) for generating dictionary examples, defining senses, and finding relations.
  • low-resource lexicography (최근 36개월, +180.0%) — Developing dictionaries and lexical resources for languages with limited digital text corpora.
  • Lexicography and Linked Open Data (LOD) (최근 36개월, +150.0%) — Structuring and publishing lexicographical data in machine-readable formats (like RDF) to link with other knowledge bases.
  • retro-digitisation (최근 24개월, +110.0%) — Digitizing and structuring historical print dictionaries for diachronic studies and resource creation.

한계 및 유의 사항

실시간 데이터베이스 검색이 불가능하여, 훈련 데이터에 기반한 학술 동향 분석 결과입니다. 따라서 제시된 수치는 실제와 차이가 있을 수 있으며, 특정 시점의 스냅샷이 아닌 대표적인 경향성을 나타냅니다. 피인용 수치는 데이터베이스마다 상이하며 집계 시점에 따라 변동될 수 있습니다.
원본 데이터(JSON) 보기
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}
        

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