International Journal of Corpus Linguistics

Papers
(The TQCC of International Journal of Corpus Linguistics is 4. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-05-01 to 2026-05-01.)
ArticleCitations
Strategies in tracing linguistic variation in a corpus of Old Irish texts (CorPH)184
A corpus-based study of anglicized neologisms in Korea45
Reproducibility, replicability, and robustness in corpus linguistics31
Review of Durrant (2023): Corpus linguistics for writing development30
Derivation and semantic autonomy21
Corpus studies of language through time21
Lexical Priming theory20
Plunged into fuel poverty16
Adverb placement in L1 and L2 spoken production15
Hypothesis-testing in corpus-assisted discourse studies14
Framing the path to net zero11
Pinpointing prescriptive impact11
Review of Egbert & Baker (2019): Using Corpus Methods to Triangulate Linguistic Analysis11
A corpus-based study into new combining forms in American English10
Register variation across text lengths9
Reproducibility and transparency in interpretive corpus pragmatics9
9
A proposal for the inductive categorisation of parenthetical discourse markers in Spanish using parallel corpora8
Grammatical complexity in film dialogue8
Review of Le Bruyn & Paquot (2021): Learner Corpus Research Meets Second Language Acquisition7
Continuum of stance in law7
Annotation uncertainty in the context of grammatical change7
Review of Dunn (2022): Natural Language Processing for Corpus Linguistics6
Using machine learning to automate data annotation in corpus linguistics6
6
5
LBiaP5
4
4
From theory to data4
Modeling the locative alternation in Mandarin Chinese4
From pre-owned printers to pristine Porsches4
A corpus-based analysis of ‘vernacular synonyms’4
Keywords of the manosphere4
Metaphorical polysemy of the Chinese color termhēi黑 “black”4
Evaluating a transparent and interpretable approach to stance detection using linguistic markers in social media data4
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