Corpus linguistics
Corpus linguistics is an empirical method for the study of language by way of a text corpus (plural corpora).[1] Corpora are balanced, often stratified collections of authentic, "real world", text of speech or writing that aim to represent a given linguistic variety.[1] Today, corpora are generally machine-readable data collections.
Corpus linguistics proposes that a reliable analysis of a language is more feasible with corpora collected in the field—the natural context ("realia") of that language—with minimal experimental interference. Large collections of text, though corpora may also be small in terms of running words, allow linguists to run quantitative analyses on linguistic concepts that may be difficult to test in a qualitative manner.[2]
The text-corpus method uses the body of texts in any natural language to derive the set of abstract rules which gover inn that language. Those results can be used to explore the relationships between that subject language and other languages which have undergone a similar analysis. The first such corpora were manually derived from source texts, but now that work is automated.
Corpora have not only been used for linguistics research, they have since the 1969 been increasingly used to compile dictionaries (starting with The American Heritage Dictionary of the English Language in 1969) and reference grammars, with A Comprehensive Grammar of the English Language, published in 1985, as a first.
Experts in the field have differing views about the annotation of a corpus. These views range from John McHardy Sinclair, who advocates minimal annotation so texts speak for themselves,[3] to the Survey of English Usage team (University College, London), who advocate annotation as allowing greater linguistic understanding through rigorous recording.[4]
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Corpus linguistics has generated a number of research methods, which attempt to trace a path from data to theory. Wallis and Nelson (2001)[21] first introduced what they called the 3A perspective: Annotation, Abstraction and Analysis.
Most lexical corpora today are part-of-speech-tagged (POS-tagged). However even corpus linguists who work with 'unannotated plain text' inevitably apply some method to isolate salient terms. In such situations annotation and abstraction are combined in a lexical search.
The advantage of publishing an annotated corpus is that other users can then perform experiments on the corpus (through corpus managers). Linguists with other interests and differing perspectives than the originators' can exploit this work. By sharing data, corpus linguists are able to treat the corpus as a locus of linguistic debate and further study.[22]
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