This article investigates how formulaic sequences fit into a constructionist approach to grammar, which is a major post-Chomskyan family of approaches to linguistic structure. The author considers whether, in this framework, formulaic sequences represent a phenomenon that is sufficiently different to warrant special status or whether they might best be studied in terms of the larger set of all constructions found in language. Based on data drawn from a large corpus of Wikipedia texts, it is argued that it is extremely difficult to form a distinct class of formulaic sequences without creating highly arbitrary boundaries. On the other hand, based on existing theoretical claims that formulaic sequences are the basis of first language acquisition, a marker of proficiency in a language, critical to the success of communicative acts and key to rapid language processing, it is argued that formulaic sequences as constructions are nevertheless significant enough to be the focus of research, and a theoretical category meriting particular attention. These findings have key repercussions both for research primarily interested in formulaic language and phraseology as well as for construction grammatical research.

Addressing a topic that has been marginal to discussions within historical linguistics, this study looks at how extent and speed of language change can be quantified meaningfully using corpus data. Looking specifically at formulaic language (understood here as word sequences that instantiate typical phrasings), a solidly data-based assessment of the speed of change within a 100-year time window is offered. This includes both a relative determination of speed (against the speed of change in lexis which is generally thought to be the fastest type of linguistic change, cf. Algeo 1980: 264; Trask and Millar 2010: 7) as well as a new independent measure of speed which is easy to interpret and therefore of high validity, while also robust and potentially applicable to any linguistic feature that can be counted in corpus data. Using data from a diachronic reference corpus of 20th century German, it is shown that change in formulaic language is very notably faster than lexical change, that the extent of change over a century is comparable in extent to contemporary inter-genre variation and that overall, the rate of change does fluctuate somewhat at the level of temporal granularity employed in this study. It is also argued that quantifying the speed of linguistic change can play an important role in building a deeper understanding of language change in general.

In this paper we describe an automated approach to enriching sentiment analysis with idiom—based features. Specifically, we automated the development of the supporting lexico—semantic resources, which include (1) a set of rules used to identify idioms in text and (2) their sentiment polarity classifications. Our method demonstrates how idiom dictionaries, which are readily available general pedagogical resources, can be adapted into purpose—specific computational resources automatically. These resources were then used to replace the manually engineered counterparts in an existing system, which originally outperformed the baseline sentiment analysis approaches by 17 percentage points on average, taking the F—measure from 40s into 60s. The new fully automated approach outperformed the baselines by 8 percentage points on average taking the F—measure from 40s into 50s. Although the latter improvement is not as high as the one achieved with the manually engineered features, it has got the advantage of being more general in a sense that it can readily utilize an arbitrary list of idioms without the knowledge acquisition overhead previously associated with this task, thereby fully automating the original approach.

This paper considers the issue of frequency consolidation in lists of different length word n-grams (i.e. recurrent word sequences) extracted from the same underlying corpus. A simple algorithm – enhanced by a preparatory stage – is proposed which allows the consolidation of frequencies among lists of different length n-grams, from 2-grams to 6-grams and beyond. The consolidation adjusts the frequency count of each n-gram to the number of its occurrences minus its occurrences as part of longer n-grams. Among other uses, such a procedure aids linguistic analysis and allows the non-inflationary counting of word tokens that are part of frequent n-grams of various lengths, which in turn allows an assessment of the proportion of running text made up of recurring chunks. The proposed procedure delivers frequency consolidation and substring reduction among word n-grams and is independent of any particular method of n-gram extraction and filtering, making it applicable also in situations where full access to underlying corpora is unavailable.

The Word Association Data Processor (WADP) is an open-source, free software package which automates key aspects of the categorisation and analysis of word association data gathered from respondents in word association tasks. The user base of this software is expected to be linguists and others working with word association data and employing a methodology similar to that presented in Fitzpatrick et. al. (2015). The WADP offers three modules. The categoriser module provides an interface for the manual categorisation of word association responses and the automatic categorisation of responses in cases where categorisations for the relevant cue-response pairs are found in a database of past categorisations. It also facilitates the automatic storage of all new ratings in the database and the tracking of respondent IDs (and categoriser/rater IDs if provided) in all input and output files. The reporter module allows the automatic creation of individual response profiles, cue profiles and primary response profiles. Finally, the administrator module performs a number of housekeeping functions such as the merging of two database files (including the resolution of conflicting entries) and producing database files from categorised output data.