Corpus-based Word Learning

Corpus-Based Word Learning is a word learning strategy that involves the systematic analysis of authentic linguistic data from corpora to inferlexical knowledge, distinguished by its reliance on empirically observed language use patterns rather than controlled or elicited data.

88

Publications

4.1K

Citations

153

Authors

89

Institutions

Publications per year

2017–2026

30

Authors

153

  1. TB
    Timothy Baldwin

    The University of Melbourne, Australia

    4 publications · 99 citations

    4

    h-index

  2. ML
    Michael L. Littman

    Rutgers, The State University of New Jersey, United States

    3 publications · 554 citations

    3

    h-index

  3. PD
    Peter D. Turney

    National Research Council Canada, Canada

    3 publications · 554 citations

    3

    h-index

  4. TN
    Thi Ngoc Yen Dang

    University of Leeds, United Kingdom

    3 publications · 84 citations

    3

    h-index

  5. FB
    Francis Bond

    NTT (Japan), Japan

    2 publications · 71 citations

    2

    h-index

1–5 of 153

Venues

  1. Journal of English for Academic Purposes

    3 publications · 100 citations

    3

    h-index

  2. Computer Assisted Language Learning

    3 publications · 204 citations

    3

    h-index

  3. ReCALL

    3 publications · 366 citations

    3

    h-index

  4. ArXiv.org

    Repository · 2 publications · 376 citations

    2

    h-index

  5. TESOL Quarterly

    2 publications · 60 citations

    2

    h-index

1–5