Corpus linguistics and theoretical linguistics

Barlow, M. G.

doi:10.1075/ijcl.16.1.02bar

Cited by 17 publications

(4 citation statements)

References 93 publications

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“…NLP recognizes that language is not just placing words in the right order but getting the meaning and deeper textual relations as well as organizing ideas into a logical textual flow. According to researchers (Barlow, 2011;Sinclair, 1991), language is not just generated according to compositional principles; it is also formulaic. Speakers possess multiple learned formulaic sequences which, according to Siyanova-Chanturia et al (2011), are important in organizing discourse and help the language producer and recipient to manage language processing.…”

Section: Multi-word Expressions As Discourse Markersmentioning

confidence: 99%

Corpus Processing of Multi-Word Discourse Markers for Advanced Learners

Liebeskind

Oleškevičienė

2023

IISIT

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Aim/Purpose. The most crucial aspects of teaching a foreign language to more advanced learners are building an awareness of discourse modes, how to regulate discourse, and the pragmatic properties of discourse components. However, in different languages, the connections and structure of discourse are ensured by different linguistic means which makes matters complicated for the learner. Background. By uncovering regularities in a foreign language and comparing them with patterns in one’s own tongue, the corpus research method offers the student unique opportunities to acquire linguistic knowledge about discourse markers. This paper reports on an investigation of the functions of multi-word discourse markers. Methodology. In our research, we combine the alignment model of the phrase-based statistical machine translation and manual treatment of the data in order to examine English multi-word discourse markers and their equivalents in Lithuanian and Hebrew translations by researching their changes in translation. After establishing the full list of multi-word discourse markers in our generated parallel corpus, we research how the multi-word discourse markers are treated in translation. Contribution. Creating a parallel research corpus to identify multi-word expressions used as discourse markers, analyzing how they are translated into Lithuanian and Hebrew, and attempting to determine why the translators made the choices add value to corpus-driven research and how to manage discourse. Findings. Our research proves that there is a possible context-based influence guiding the translation to choose a particle or other lexical item integration in Lithuanian or Hebrew translated discourse markers to express the rhetorical domain which could be related to the so-called phenomenon of “over-specification.” Recommendations for Practitioners. The comparative examination of discourse markers provides language instructors and translators with more specific information about the roles of discourse markers. Recommendations for Researchers. Understanding the multifunctionality of discourse markers provides new avenues for discourse marker application in translation research. Impact on Society. The current study may be a useful method to strengthen students’ language awareness and analytic skills and is particularly important for students specializing in English philology or translation. Beyond the empirical research, an extensive parallel data resource has been created to be openly used. Future Research. It should be noted that the observed phenomenon of “over-specification” could be analyzed further in future research.

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Section: Multi-word Expressions As Discourse Markersmentioning

confidence: 99%

Corpus Processing of Multi-Word Discourse Markers for Advanced Learners

Liebeskind

Oleškevičienė

2023

IISIT

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“…Neither is there a “unifying theory binding together corpus linguistics analyses” (Barlow, 2011, p. 5), nor are there uniform practices or techniques about how one “does” corpus linguistics. Corpus linguistics can be used in a primarily qualitative design to generate theory inductively or in a primarily quantitative, positivist design to test theory on language (McEnery & Wilson, 2001, p. 110).…”

Section: Computer-aided Approaches For the Analysis Of Textual Datamentioning

confidence: 99%

“…The research questions corpus linguistics can answer address the association of textual patterns either with other textual patterns or with contextual patterns (Biber et al, 1998). For example, corpus linguistics can study language use in a particular text genre, in a particular kind of discourse, or in a particular social or communicative context (Barlow, 2011). Linguists of all persuasions have used these techniques in qualitative or quantitative designs, ranging from semantic studies of near-synonyms (Liu, 2010) to sociolinguistic studies of language variation (Kachru, 2008) and language change (Baker, 2009).…”

Section: Computer-aided Approaches For the Analysis Of Textual Datamentioning

confidence: 99%

Taming Textual Data: The Contribution of Corpus Linguistics to Computer-Aided Text Analysis

Pollach¹

2011

Organizational Research Methods

132

108

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Corpus linguistics studies real-life language use on the basis of a text corpus, drawing on both quantitative and qualitative text analysis techniques. This article seeks to bridge the gap between the social sciences and linguistics by introducing the techniques of corpus linguistics to the field of computer-aided text analysis. The article first discusses the differences between corpus linguistics and computer-aided text analysis, which is divided into computer-aided content analysis and computer-aided interpretive textual analysis. It then outlines the techniques of corpus linguistics for exploring textual data. In an exemplary analysis of letters to shareholders, the article demonstrates how these techniques can be applied to compare letters to shareholders from two different years. The article concludes with a discussion of the strengths and limitations of corpus linguistics for management and organization studies.

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“…One of the most interesting discoveries in applied linguistics in the last three decades, driven by corpus linguistic analysis, was establishing that language is not typically generated word-by-word, but rather it is largely formulaic in nature (Barlow 2011). Starting with early discussions by scholars such as Pawley and Syder (1983) and Sinclair (1991) (open-choice principle vs idiom principle), the area of formulaic language 1 has exploded, generating a vast number of research studies and books (e.g.…”

Section: Introductionmentioning

confidence: 99%

Formulaic language is not all the same: comparing the frequency of idiomatic phrases, collocations, lexical bundles, and phrasal verbs

Vilkaitė

2016

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Formulaic language is widely acknowledged to be a central part of a language. However, it is heterogeneous in nature, made up of various formulaic categories with their own characteristics and behaviour. A first step towards systematically describing the relationship between these categories is to describe their distribution in language. This study investigated the frequency of occurrence of four categories of formulaic sequences: collocations, phrasal verbs, idiomatic phrases, and lexical bundles. Together the four categories made up about 41% of English, with lexical bundles being by far the most common, followed by collocations, idiomatic phrases and phrasal verbs. There were differences in the frequencies of each category in the overall corpus, and also in the four registers analysed (academic prose, fiction, newspaper language, and spoken conversation). Language mode (spoken/written) had a substantial effect on the frequency distribution of the categories as well.

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Corpus linguistics and theoretical linguistics

Cited by 17 publications

References 93 publications

Corpus Processing of Multi-Word Discourse Markers for Advanced Learners

Corpus Processing of Multi-Word Discourse Markers for Advanced Learners

Taming Textual Data: The Contribution of Corpus Linguistics to Computer-Aided Text Analysis

Formulaic language is not all the same: comparing the frequency of idiomatic phrases, collocations, lexical bundles, and phrasal verbs

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