International Journal of Corpus Linguistics - Volume 18, Issue 4, 2013

Since usage-based theories such as cognitive grammar assume an intimate relationship between mental representations of grammar and the processing of instances of language (usage events), corpora have an important role in the development of grammatical analyses. One consequence of relying on corpus data is that individual differences in usage tend to be obscured. To overcome this problem and investigate individual differences in spoken usage, we examine a large corpus consisting of the spoken output of six White House press secretaries. The results provide strong evidence that within this one particular discourse context the patterns of speech of each individual are clearly recognisable. Furthermore, these idiolectal preferences are consistent and are maintained over a period of at least a year or two. In addition, we briefly explore some theoretical consequences and possible explanations for the disparity found between the speech of the individual and that of the discourse community.

A powerful discourse-pragmatic agent of grammatical change in English since the mid-twentieth century has been the increasing acceptance of colloquialism. Little is known, however, about its influence on grammatical developments in regional varieties of World English other than the two inner circle ‘supervarieties’, British and American English. This paper reports findings from a corpus-based study of three grammatical categories known to be undergoing a colloquialism-related rise in contemporary English, across a range of registers in ten World Englishes: quasi-modals (have to, have got to, be going to, want to), get-passives, and first person plural inclusive let’s. In each case comparisons are drawn with non-colloquial variants: modals (must, should, will, shall), be-passives, and let us. Subsequent functional interpretation of the data is used to explore the effect upon the quantitative patterns identified of the phenomenon of colloquialism and of further factors with which it interacts (including Americanism, prescriptivism, and evolutionary status).

This study aims to develop a new computing method for extracting contiguous phraseological sequences (PSs) of various lengths from academic text corpora by measuring internal associations of n-grams. We construct a new normalizing algorithm of probability-weighted average for refining the MI measure and enhancing precision in extracting PSs from corpora. This computing method is applied to the data in a medium-sized text corpus of academic English. Results indicate that the resultant new MI measure can provide statistics which better reveal internal associations within an n-gram, regardless of size. Lexico-grammatical sequences extracted with this method are more complete and less arbitrary in terms of grammar and semantics. The method can be applied to treating a variety of linguistic phenomenon, ranging from well-established phrases to likely phrasal entities, thus having potentially practical applications in corpus-based studies of phraseology and natural language processing.

This paper explores two tools and methods for keyword extraction. As several tools are available, it makes a comparison of two widely used tools, namely Lexico3 (Lamalle et al. 2003) and WordSmith Tools (Scott 2013). It shows the importance of keywords and discusses recent studies involving keyword extraction. Since no previous study has attempted to compare two different tools, used by different language communities and which use different methodologies to extract keywords, this paper aims at filling the gap by comparing not only the tools and their practical use, but also the underlying methodologies and statistics. By means of a comparative study on a small test corpus, this paper shows major similarities and differences between the tools. The similarities mainly concern the most typical keywords, whereas the differences concern the total number of significant keywords extracted, the granularity of both probability value and typicality coefficient and the type of the reference corpus.

This article examines the distribution of the nucleus around selected formulaic expressions in the IBM/Lancaster Spoken English Corpus (SEC). The study reveals the presence of a positional bias such that formulaic expressions found at the end of intonation units are more likely to receive the nucleus than those found at the beginning. Amongst the formulaic expressions located at the end of intonation units, 70 percent have the nucleus assigned to the last lexical word of the expressions. For the remaining cases, the obligatory nuclei are found either on the lexical words immediately preceding the expressions or on the first words, the degree words or the flexible slots within the expressions. The study shows how prosodically annotated corpora may facilitate research on the prosody of formulaic expressions. At the same time, it also raises awareness of the issues confronting this new research avenue.