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Corpus Linguistic Analysis: How Far Can We Go?

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Computer Supported Qualitative Research (ISQR 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 621))

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Abstract

The present paper aims to explore methodological approaches to the examination of corpus linguistic data with particular attention to higher-level analysis. Fundamental assumptions in corpus linguistics are questioned, including the concept of repetition and so of token and type, parsing of items, the use and interpretation of metaphor, and the sociolinguistic and pragmatic elements in all utterances. Using purposely collected corpus data from very limited corpora, the paper aims to underline the importance of qualitative approaches to linguistic analysis even in the ostensibly highly quantitative field of ‘traditional’ corpus linguistics. Preliminary conclusions suggest that the complexity and richness of corpus linguistic data make qualitative analysis very demanding, but of unquestionable potential significance. The final proposal is for a small-scale corpus approach to accompany the mass linguistic data of large corpora, offering different analyses and results that might be valuable for fruitful comparison and triangulation

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Notes

  1. 1.

    Another, more significant example of this is the very real difficulty in defining a word, or in identifying types as being truly different from other tokens already occurring in the corpus: a typing error might be an intentional, rhetorical variation, or a personal idiomatic peculiarity. The current paper is partly a result of meeting precisely this difficulty in data from a small corpus (see Sect. 2).

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Correspondence to Richard Chapman .

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Chapman, R. (2018). Corpus Linguistic Analysis: How Far Can We Go?. In: Costa, A., Reis, L., Souza, F., Moreira, A. (eds) Computer Supported Qualitative Research. ISQR 2017. Advances in Intelligent Systems and Computing, vol 621. Springer, Cham. https://doi.org/10.1007/978-3-319-61121-1_35

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  • DOI: https://doi.org/10.1007/978-3-319-61121-1_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61120-4

  • Online ISBN: 978-3-319-61121-1

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