Applied Corpus Linguistics最新文献

The launch of a language's first comprehensive general corpus promises a sea-change in teaching and learning resources. Effective transition from corpus to classroom is not necessarily straightforward, though; expert and end-user input is essential for the potential of the corpus resource to be realised. This paper outlines the process by which fit-for-purpose vocabulary lists were derived from the new National Corpus of Contemporary Welsh (Corpws Cenedlaethol Cymraeg Cyfoes – CorCenCC). The immediate purpose in this case was to inform the revision of A1 and A2 level course materials for adult learners. A longer-term aim was to put in place a method by which vocabulary lists for more advanced level learners and learners of different ages could be extracted and developed from the corpus. The new corpus means that for the first time, the Welsh language curriculum is able to use word frequency information; teaching and assessment materials in major languages have been informed by word frequencies for several decades. Raw frequency lists, though, include troublesome content, and can exclude items with high relevance to learners. This paper demonstrates how, by working in partnership, Welsh language curriculum writers, assessors, language experts and corpus linguists can effectively manipulate corpus data into curriculum content. The methods and approaches reported here are replicable for use in other language contexts.

The purpose of this work is to revise and expand an aeronautical meteorology glossary, available at REDEMET, a homepage hosted on the Department of Airspace Control website, taking into consideration corpus data in the field. For that, to best meet the needs of institutions and users, data were compiled from some segments of the Aeronautical Meteorology domain. During the compilation of this corpus, it was noticed that there was a great scarcity of specialized sources of this Aviation subdomain in English and, mainly, in Portuguese, including material by the Department of Airspace Control (DECEA), the only official Brazilian institution with the role of regulating standards relevant to Aeronautical Meteorology. By taking into account that a given government institution is considered an authoritative source concerning terms used in a specialized domain, it would be advisable to align professional and academic expertise, and institutional interests. Therefore, based on contributions of corpus linguistics theories, terminology, and institutional translation, this work relied on established parameters for the compilation and processing of information for inclusion in the corpus, and focused, in this first stage, on the selection of candidate terms, according to corpus analysis. The first results showed that institutional and academic segments present some subtleties regarding terminology, as, on the one hand, some words are more specific to the academic register and, on the other hand, there are different uses of terms in the institutional setting, by ICAO, WMO, or FAA.

This paper reports on an application of a multimodal corpus-based study into the effectiveness of public health information about COVID-19 for speakers of English as an additional language (EAL) in the UK. A corpus of information tweets from 13 UK public health agencies totalling 560,000 words, with concomitant images and videos, was collected between March 2020 and February 2021. The most frequent n-grams occurring across all 13 public health agencies, and sample images occurring alongside these, were identified. In this study, we examine how images and videos combine with the phraseology to shape these COVID-19 public health information messages. Following this, six illustrative tweets were used as prompts for three focus groups of EAL participants based in the UK representing a range of first languages and occupations. Data from the focus groups was analysed in order to identify how common public health phraseology and images were received, understood and responded to by participants and how they felt they could be amended to increase their effectiveness for EAL speakers. We conclude with suggestions for making the language of public health messages simpler and more direct, aligning images more clearly with the language used and removing linguistic ambiguity. These recommendations for how such messaging could be improved in future public health campaigns could ensure a more effective and inclusive public health response.

There is a need for more publicly available corpora of legal language. To help fill this gap, we have developed the Corpus of U.S. State Statutes, or CorUSSS, a new corpus comprising the statutory code from all 50 U.S. states. In total the corpus contains 1,785,742 texts, each of which represents the statutory text associated with a unique Universal Citation in one of the 50 U.S. states’ codes. This corpus provides us with the ability to explore language use in statutes within or across all 50 states. After motivating the need for this corpus, we describe its design and the methods we used to collect, clean and store the texts. We then report on a case study that illustrates the utility of this corpus for addressing important questions in statutory interpretation by investigating whether the word information can be used to refer to statements that are non-factual. We conclude with a call for researchers in law and corpus linguistics to rely on both legal and ordinary language when investigating questions of interpretation.

This article discusses how corpus linguistic methods were adapted for critical research examining the content and pedagogy of human rights learning within texts approved for classroom use under Japan's official social studies curriculum. While human rights concepts are common facets of official curricula, designed to address social injustice and foster peaceful coexistence, such learning has undergone critical re-examination as being complicit in perpetuating social injustice. Drawing upon Bernstein's sociology of the curriculum and based on a corpus of upper-secondary curricular texts, this research is a pragmatic mixing of quantitative and qualitative methods that sought to understand the curriculum's potential role within learning for human rights. By way of empirical example, the article aims to inform future critical research designs within the sociology of the curriculum. Corpus-based analytical techniques were vital in demonstrating how the structuring of textbook human rights limits student engagement with social justice issues and functions instead to inculcate pride in Japanese ethnonationality.

This paper sets forth a quantitative analysis of expressions of epistemicity, a category covering the expression of commitment to the information transmitted and comprising epistemic modality and evidentiality, in a corpus of 400 newspaper articles from The Guardian concerning the COVID-19 pandemic. 200 articles were written in April 2020; the other 200 were written between January and April 2022, after massive vaccination and an extraordinary increase in medical knowledge. The analysis distinguishes between a number of subtypes of epistemic expressions and three kinds of authorial voice. The results show that the April 2020 articles contain more epistemic expressions, of both weak commitment (might, perhaps, apparently…) and strong commitment (know, clearly, surely…), which suggests a greater need to distinguish the known from the unknown in this period, due to the pervasive state of uncertainty. The analysis has social implications, since it gives readers an opportunity to appreciate the careful assessments of epistemicity found in the corpus and therefore to consider the convenience of obtaining information from quality media. These social implications, together with the methodology of the analysis, contribute to the potential of the paper for pedagogical applications.

As recent years have witnessed increasing pressure on personal finances, compounded by the current cost of living crisis, online forums have become an important resource for people dealing with financial precarity. In this article, we offer a corpus linguistic analysis of data from MoneySavingExpert.com, the UK's largest online money management advice forum, studying 207 threads and 41.4 million words of text posted from 2005 to 2021. Through measures of word frequency and word association, we uncover similarities and differences in language use on the debt-free wannabe (DFW) and mortgage-free wannabe (MFW) forums. Our findings show that the DFW forum focuses on interactive exchanges involving requests for help and offers of advice, while the MFW forum is characterised by goal setting and community building. We thus contribute new insights into the discursive construction of debt in digital media and provide further understanding of the role online forums play in supporting vulnerable people.

This short communication discusses the impact of ChatGPT on the field of corpus linguistics, particularly its potential as a concordancer. As a corpus linguist and app developer, the author reflects on how ChatGPT's ease of use, efficiency, and popularity could challenge traditional concordancers, and explores ways in which ChatGPT could be used to generate concordances and frequency lists.

This article explores the potential advantages of corpora over generative artificial intelligence (GenAI) in understanding language patterns and usage, while also acknowledging the potential of GenAI to address some of the main shortcomings of corpus-based data-driven learning (DDL). One of the main advantages of corpora is that we know exactly the domain of texts from which the corpus data is derived, something that we cannot track from current large language models underlying applications like ChatGPT. We know the texts that make up large general corpora such as BNC2014 and BAWE, and can even extract full texts from these corpora if needed. Corpora also allow for more nuanced analysis of language patterns, including the statistics behind multi-word units and collocations, which can be difficult for GenAI to handle. However, it is important to note that GenAI has its own strengths in advancing our understanding of language-in-use that corpora, to date, have struggled with. We therefore argue that by combining corpus and GenAI approaches, language learners can gain a more comprehensive understanding of how language works in different contexts than is currently possible using only a single approach.