The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Collocations in Corpus‐Based Language Learning Research: Identifying, Comparing, and Interpreting the Evidence
Open accessAbstract
This article focuses on the use of collocations in language learning research (LLR). Collocations, as units of formulaic language, are becoming prominent in our understanding of language learning and use; however, while the number of corpus‐based LLR studies of collocations is growing, there is still a need for a deeper understanding of factors that play a role in establishing that two words in a corpus can be considered to be collocates. In this article we critically review both the application of measures used to identify collocability between words and the nature of the relationship between two collocates. Particular attention is paid to the comparison of collocability across different corpora representing different genres, registers, or modalities. Several issues involved in the interpretation of collocational patterns in the production of first language and second language users are also considered. Reflecting on the current practices in the field, further directions for collocation research are proposed.
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R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Longman Grammar of Spoken and Written English
Broussard, K. M., Biber, D., Johansson, S., Leech, G., Conrad, S., & Finegan, E. (2000) · TESOL Quarterly · doi:10.2307/3587792 · Cited by 8,193
Word association norms, mutual information, and lexicography
Church, K., & Hanks, P. (1990) · doi:10.5555/89086.89095 · Cited by 3,590
Corpus, Concordance, Collocation
Green, P. N. (1992) · Cited by 3,465
Formulaic Language and the Lexicon
Wray, A. (2002) · doi:10.1017/cbo9780511519772 · Cited by 2,873
Corpus, Concordance, Collocation
Odlin, T., & Sinclair, J. (1994) · The Modern Language Journal · doi:10.2307/330144 · Cited by 2,297
Ellis, N. C. (2002) · Studies in Second Language Acquisition · doi:10.1017/s0272263102002024 · Cited by 2,230
Corpora in Applied Linguistics
Hunston, S. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9781139524773 · Cited by 1,616
Stewart, E. C. (1982) · Language Sciences · doi:10.1016/s0388-0001(82)80008-9 · Cited by 1,248
Words and Phrases: Corpus Studies of Lexical Semantics
Stubbs, M. (2001) · Cited by 1,174
Cited by
Ukrainian refugees in Polish press
Zawadzka-Paluektau, N. (2023) · Discourse & Communication · doi:10.1177/17504813221111636 · Cited by 82
Saito, K. (2020) · Language Learning · doi:10.1111/lang.12387 · Cited by 74
Tao, Y., Finnerty, S., Robinson, S., Philpot, R., Shaw, H., & Levine, M. (2026) · doi:10.21203/rs.3.rs-9518900/v1 · Cited by 1
Metadata
- Authors
- Gablasova, D., Brezina, V., & McEnery, T.
- Venue
- Language Learning
- Publisher
- Wiley
- Published
- 2017-02-20
- Volume
- 67
- Issue
- S1
- Pages
- 155-179
- ISSN
- 0023-8333 (ISSN-L)
- 1467-9922
- OpenAlex
- W2582614075
- Cited by
- 482
- References
- 53
- FWCI
- 52.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
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