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Corpus Concordance Analysis×Keyness Analysis×
DziedzinaJęzykoznawstwoJęzykoznawstwo
RodzinaProcess / pipelineProcess / pipeline
Rok powstania19911997
TwórcaCorpus linguists (John Sinclair; Paul Baker)Mike Scott
TypCorpus-based descriptive analysis of word usage in contextCorpus comparison of relative word frequencies
Źródło pierwotneBaker, P. (2006). Using Corpora in Discourse Analysis. Continuum. ISBN: 9780826477248Scott, M. (1997). PC analysis of key words — and key key words. System, 25(2), 233–245. DOI ↗
Inne nazwyConcordance Analysis, KWIC Analysis, Keyword-in-Context AnalysisKeyword Analysis, Corpus Keyness, Keyness Statistics
Pokrewne43
PodsumowanieCorpus concordance analysis is a core corpus-linguistic technique that retrieves every occurrence of a search word or phrase from a large body of machine-readable text and displays them in keyword-in-context (KWIC) format — the target term aligned in a central column with its surrounding co-text. By reading and sorting these lines, analysts uncover the recurrent patterns, collocations, and meanings of words as they are actually used, grounding linguistic claims in attested evidence rather than introspection.Keyness analysis identifies the words that are characteristically frequent (or infrequent) in a target corpus relative to a reference corpus, using statistical tests to measure how unexpected each word's frequency is. Introduced by Mike Scott in 1997, it answers the question 'what is this text or collection distinctively about?' and is a central technique in corpus linguistics and corpus-assisted discourse analysis for surfacing the salient vocabulary of a genre, period, author, or social group.
ScholarGateZbiór danych
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  1. v1
  2. 3 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Corpus Concordance Analysis · Keyness Analysis. Pobrano 2026-06-24 z https://scholargate.app/pl/compare