Abstract This study presents a method for identifying words that appear in corpus data earlier than their first date of attestation in dictionaries. We demonstrate the application of this method based on a large diachronic corpus, the TV Corpus, and the Oxford English Dictionary (OED). Combining automatic extraction of candidate terms from the TV Corpus with comprehensive manual analysis and verification, the method identifies 32 words that were used in TV series before their first attestation in the OED. We present a detailed discussion of these words, analysing their distribution across decades and genres of the TV Corpus, their origins, semantic domains and word-formation processes. We also present extracts with their first uses in the TV Corpus and analyse how the words were presented to the large and anonymous mass audience. Our study shows that the method we present is suitable for identifying early attestations of words in large corpora, even though in the case of the TV Corpus, a great deal of manual analysis and verification is needed. In addition, we argue that TV series and other types of fictional texts are an important resource for studying the coinage and spread of terms, due to their function and the fact that they address a mass audience.

Abstract In this research article we introduce the S outh A sian On line E nglishes (SAOnE) corpus representing four South Asian countries, i.e. Bangladesh, India, Pakistan, and Sri Lanka, and two native English-speaking countries, i.e. the UK and the USA. We have used semi-automatic and manual methods to collect data from three internet registers, i.e. newspaper comments, web forums and tweets, and a collection of internet sub-registers which we label as blogs and websites. Additionally, we have collected text messages using online freelance hiring platforms from each of the South Asian countries mentioned above. Each register category in the corpus consists of approximately 1 million words per register per country, except text messages, which contains around 500,000 words per country and only includes the four South Asian countries. We have verified the origin of website and blog links, authors of Twitter, and where possible of commenters and web forum users to make sure that only local content of each country is included. The corpus features some indigenous language content, which is tagged. In addition to the description of this dataset, we also present a pilot study analysing three discourse particles, namely na , neh , and yaar . The discourse particles na and yaar are native to Hindi/Urdu, while neh is based on a Sinhala negation marker. Our analysis indicates that na and neh have similarities in terms of their position in the clause/utterance. However, neh is confined to Sri Lanka while the Hindi/Urdu based discourse particles are also used in our Twitter data from Sri Lanka and Bangladesh. The use of these discourse particles in Bangladeshi tweets shows the influence of Indian culture through Bollywood celebrities. Of the Hindi/Urdu discourse particles yaar and na , yaar is preferred in Pakistan while na is preferred in India; additionally, yaar is used at the start of the clause more often in our Pakistani data. Lastly, we discuss the implications of the pilot study, the advantages of the type of data used for the pilot study, and future research directions.

Sciendo provides publishing services and solutions to academic and professional organizations and individual authors. We publish journals, books, conference proceedings and a variety of other publications.

Sciendo provides publishing services and solutions to academic and professional organizations and individual authors. We publish journals, books, conference proceedings and a variety of other publications.

Bridging the gap between university and upper secondary school English studies : The ULE project

Abstract This study examines for the first time a very large set of psychological verbs and their derived adjectives in English. To determine whether an item is an adjective or not, we take the standard structural criteria of morphological (-ly or un-), morpho-syntactic (very, -er/-est or more/most) and syntactic (seem, look, or feel) characteristics. As for the data, we selected three data bases and gathered those containing certain items in specific contexts, such as whether the item in question takes a -ly or un- affix, or a comparative or superlative form, or follows seem, look or feel. We took dictionaries as our source of criteria in checking whether an item was perceived to be an adjective. As a result, we found some hierarchy within adjectives as to whether they take morphological, morpho-syntactic, or syntactic characteristics. The most powerful determinant of adjectives is the morphological characteristic -ly.

Sciendo provides publishing services and solutions to academic and professional organizations and individual authors. We publish journals, books, conference proceedings and a variety of other publications.

This monograph presents a highly accessible, concise, and vivid discussion of the main issues of using the web as a corpus, ranging from the theoretical implications it has for corpus linguistics as a field to the various tools and methods that have been appropriated and developed by web corpus linguists over the past fifteen years.The successful combination of theory and practice by the author is complemented by a brief historical survey of the development of the web corpus approach.The book is meant as an introduction to the subject for students in any language-related programmes, and as a resource for "teachers or researchers in the humanities" more generally; accordingly, the focus is on how to use existing tools rather than how to create new ones (p. 1).To be sure, Web as corpus is suitable for readers with limited technical skills and little previous knowledge of corpus linguistics, but more experienced corpus linguists are likely to find a few jewels in there as well.The book comprises seven chapters, of which the first two are introductory and the last one is very short.Each chapter is followed by study questions and activities, which mainly do not go beyond the text itself, and a useful list of suggestions for further reading.The first chapter explains the author's position that corpus linguistics is an "approach" with certain theoretical implications about language and with its own methods (p. 6).The bulk of the chapter deals with the basics of corpus linguistics: key concepts are explained together with the different steps of corpus creation, some basic analyses typically conducted on corpora, and certain statistical formulae.Space is also given to a discussion of accepted standards in corpus compilation, particularly the use of authentic language, representativeness, balance (in terms of topics, genres, publishing dates, and mediums), and large enough database size.The initial chapter attends to the needs of readers with no previous contact with corpora, but is largely superfluous to experienced corpus linguists.