By Douglas Biber, Randi Reppen
The Cambridge guide of English Corpus Linguistics (CHECL) surveys the breadth of corpus-based linguistic examine on English, together with chapters on collocations, phrasing, grammatical edition, ancient swap, and the outline of registers and dialects. the main leading edge facets of the CHECL are its emphasis on severe dialogue, its particular evaluate of the cutting-edge in each one sub-discipline, and the inclusion of empirical case reports. whereas every one bankruptcy encompasses a extensive survey of earlier examine, the first concentration is on an in depth description of an important corpus-based stories during this quarter, with dialogue of what these reports came upon, and why they're very important. each one bankruptcy additionally incorporates a severe dialogue of the corpus-based equipment hired for examine during this sector, in addition to an specific precis of recent findings and discoveries.
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Additional info for The Cambridge Handbook of English Corpus Linguistics
G. accurate metadata for all of the texts in the corpus). And this is especially true when the corpus is created by a small team and with limited resources. Consider first the issue of accuracy in document-level metadata. The Brown Corpus is composed of just 500 texts, and it is very easy to achieve 100 percent accuracy in terms of metadata. 9 percent accurate in terms of metadata, there are potentially 50 or 100 texts that might have the wrong date, title, author, or genre classification. If one is researching the very first occurrence of a word or phrase or a 6 COHA = Corpus of Historical American English – a historical, “companion” corpus for COCA; see Davies 2012a, 2012b, forthcoming.
The only question, then, is whether we will take advantage of the new resources that are certain to come our way. 31 2 Computational tools and methods for corpus compilation and analysis Paul Rayson 1 Introduction The growing interest in corpus linguistics methods in the 1970s and 1980s was largely enabled by the increased power of computers and the use of computational methods to store and process language samples. Before this, even simple methods for studying language such as extracting a list of all the different words in a text and their immediate contexts was incredibly time consuming and costly in terms of human effort.
1) is the 400-million-word Corpus of Historical American English (COHA; see Davies 2012a, 2012b, forthcoming). I have also suggested that for very recent changes in English, the only reliable monitor corpus – which maintains the same genre balance from year to year (a crucial factor, which virtually all previous studies seem to have overlooked) and which is large enough to study a wide range of phenomena – is the Corpus of Contemporary American English (COCA; see Davies 2011). In terms of dialectal variation, the International Corpus of English (Greenbaum 1996; Hundt and Gut 2012) can describe the range of variation about as well as other 1-million-word corpora, as we discussed in Section 3.