Corpus Representativeness
Jesse Egbert, Douglas Biber, Bethany Gray · Cambridge University Press eBooks · 2022
As discussed in Chapter 1, corpus representativeness depends on two sets of considerations: domain considerations and distribution considerations. Domain considerations focus on describing the arena of language use, and operationally specifying a set of texts that could potentially be included in the corpus. The linguistic research goal, which involves both a linguistic feature and a discourse domain of interest, forms the foundation of corpus representativeness. Representativeness cannot be designed for or evaluated outside of the context of a specific linguistic research goal. Linguistic parameter estimation is the use of corpus-based data to approximate quantitative information about linguistic distributions in the domain. Domain considerations focus on what should be included in a corpus, based on qualitative characteristics of the domain. Distribution considerations focus on how many texts should be included in a corpus, relative to the variation of the linguistic features of interest. Corpus representativeness is not a dichotomy (representative or not representative), but rather is a continuous construct. A corpus may be representative to a certain extent, in particular ways, and for particular purposes.