Keyness Analysis
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Scott, M. (1997). PC analysis of key words — and key key words. System, 25(2), 233–245. · DOI 10.1016/S0346-251X(97)00011-0
- Baker, P. (2006). Using Corpora in Discourse Analysis. Continuum. · ISBN 9780826477248
- Gabrielatos, C. (2018). Keyness analysis: Nature, metrics and techniques. In C. Taylor & A. Marchi (Eds.), Corpus Approaches to Discourse: A Critical Review (pp. 225–258). Routledge. · ISBN 9781138895157
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.