Book contents
- The Cambridge Handbook of English Corpus Linguistics
- Cambridge Handbooks in Language and Linguistics
- The Cambridge Handbook of English Corpus Linguistics
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Major Corpora Cited in the Handbook
- Introduction
- Part I Methodological Considerations
- Part II Corpus Analysis of Linguistic Characteristics
- 4 Intonation and Other Prosodic Features
- 5 Keyword Analysis
- 6 Phraseology and Collocation
- 7 Lexical and Phraseological Complexity in Learner Language
- 8 Grammatical Variation
- 9 Grammatical Change
- 10 Discourse Analysis Using Corpus-Assisted Methodologies
- 11 Corpus Pragmatics
- 12 Multimodal Corpora
- Part III Corpus Analysis of Varieties
- Part IV Other Applications of Corpus Analysis
- Index
- References
10 - Discourse Analysis Using Corpus-Assisted Methodologies
from Part II - Corpus Analysis of Linguistic Characteristics
Published online by Cambridge University Press: 08 July 2026
Book contents
- The Cambridge Handbook of English Corpus Linguistics
- Cambridge Handbooks in Language and Linguistics
- The Cambridge Handbook of English Corpus Linguistics
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Major Corpora Cited in the Handbook
- Introduction
- Part I Methodological Considerations
- Part II Corpus Analysis of Linguistic Characteristics
- 4 Intonation and Other Prosodic Features
- 5 Keyword Analysis
- 6 Phraseology and Collocation
- 7 Lexical and Phraseological Complexity in Learner Language
- 8 Grammatical Variation
- 9 Grammatical Change
- 10 Discourse Analysis Using Corpus-Assisted Methodologies
- 11 Corpus Pragmatics
- 12 Multimodal Corpora
- Part III Corpus Analysis of Varieties
- Part IV Other Applications of Corpus Analysis
- Index
- References
Summary
The aim of corpus-assisted discourse studies (CADS) is the uncovering, in the discourse type under study, of what we call nonobvious meaning, that is, meaning which might not be readily available to naked-eye perusal. By combining the quantitative approach, that is, statistical overviews of large amounts of the discourse in question with the more qualitative approach typical of discourse analysis, that is, the close analysis of particular stretches of discourse, it may be possible to access such nonobvious meanings. This chapter describes a set of CADS case studies into the facework performed during media and political interaction, from early work on White House press briefings to contrastive examinations of the facework typical of the US State Department and Chinese Foreign Ministry briefings which envisage not just the study of interpersonal im/politeness but also the performance of ‘national facework’. The facework involved in all these settings is multifaceted and complex. Firstly it is not always collaborative, indeed it is often downright competitive, and impoliteness is not uncommon, and it also comprises a mixture of personal, group and vicarious facework. The corpora employed in these studies are also multimedia in that videos of the briefings are also mostly available alongside the transcripts.
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- The Cambridge Handbook of English Corpus Linguistics , pp. 203 - 223Publisher: Cambridge University PressPrint publication year: 2026
References
Baker, P., Gabrielatos, C., & McEnery, T. 2013. Discourse analysis and media attitudes: The representation of Islam in the British press. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Biber, D., Johansson, S., Leech, G., Conrad, S., & Finegan, E. 1999. Longman grammar of spoken and written English. London: Longman.Google Scholar
Blaxill, L. 2018. Introduction. From “post-democracy” to “post-truth” in political language. Textus, 31(1), 57–66.Google Scholar
Brindle, A. 2016. The language of hate: A corpus linguistics analysis of white supremacist language. New York: Routledge.CrossRefGoogle Scholar
Brown, G., & Yule, G. 1983. Discourse analysis. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Brown, P., & Levinson, S. 1987. Politeness: Some universals in language usage. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Cockcroft, R., & Cockcroft, S. 2005. Persuading people: An introduction to rhetoric, 2nd ed. London: Palgrave Macmillan.Google Scholar
Davies, M. 2009. The 385+ million word Corpus of Contemporary American English (1990–2008+). International Journal of Corpus Linguistics, 14(2), 159–190.CrossRefGoogle Scholar
Demata, M. 2018. “I think that maybe I wouldn’t be here if it wasn’t for Twitter”: Donald Trump’s populist style on Twitter. Textus, 31(1), 67–90.Google Scholar
Duguid, A. 2009a. Loud signatures: Comparing evaluative discourse styles – patterns in rants and riffs. In Romer, U. & Schulze, R. (Eds.), Exploring the lexis-grammar interface (pp. 289–315). Amsterdam: John Benjamins.CrossRefGoogle Scholar
Duguid, A. 2009b. Insistent voices, government messages. In Morley, J. & Bayley, P. (Eds.), Corpus-assisted discourse studies on the Iraq conflict: Wording the war (pp. 234–260). London: Routledge.Google Scholar
Duguid, A. 2015. Public apologies and media evaluations. In Bondi, M., Cacchiani, S., & Mazzi, D. (Eds.), Discourse in and through the media: Recontextualizing and reconceptualizing expert discourse (pp. 146–169). Newcastle: Cambridge Scholars Publishing.Google Scholar
Francis, W. N. 1982. Problems of assembling and computerising large corpora. In Johansson, S. (Ed.), Computer corpora in English language research (pp. 7–24). Bergen: Norwegian Computing Centre for the Humanities.Google Scholar
Halliday, M., & Mattiessen, M. 2004. An introduction to functional grammar, 3rd ed. London: Arnold.Google Scholar
Hoey, M. 2005. Lexical priming: A new theory of words and language. London: Routledge.Google Scholar
Hunston, S., & Thompson, G. (Eds.) 2000. Evaluation in text. Oxford: Oxford University Press.CrossRefGoogle Scholar
Louw, W. 1993. Irony in the text or insincerity in the writer? The diagnostic potential of semantic prosodies. In Baker, M., Francis, G., & Tognini-Bonelli, E. (eds.) Text and technology: In honour of John Sinclair (pp. 157–176). Amsterdam: John Benjamins.CrossRefGoogle Scholar
Marakhovskaiia, M. & Partington, A. 2019. National face and facework in China’s foreign policy: A corpus assisted study of Chinese foreign affairs press conferences. Bandung: Journal of the Global South, 6, 105–131.CrossRefGoogle Scholar
Marchi, A. 2018. Dividing up the data: Epistemological, methodological and practical impact of diachronic segmentation (pp. 174–196). In Taylor, C. & Marchi, A. (Eds.), Corpus approaches to discourse: A critical review. London: Routledge.CrossRefGoogle Scholar
Mautner, G. 2016. Mad about method: Challenges and opportunities at the CDA/CL interface. Talk given at the III Corpora and Discourse International Conference, Siena, July. https://research.wu.ac.at/de/activities/mad-about-method-challenges-and-opportunities-at-the-cdacl-interf-12.Google Scholar
Napoletano, A., & Aiezza, M.-C. 2018. The press war in the post-truth era: A corpus-assisted CDA of the discourse of US political analysts on Trump’s figure and policy. Textus, 31(1), 91–118.Google Scholar
Partington, A. (Ed.) 2010. Modern diachronic corpus-assisted discourse studies on UK newspapers. Corpora, 5(2), 83–108.CrossRefGoogle Scholar
Partington, A. 1998. Patterns and meanings: using corpora for English language research and teaching. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Partington, A. 2017. Varieties of non-obvious meaning in CL and CADS: From ‘hindsight post-dictability’ to sweet serendipity. Corpora, 12(3), 339–367.CrossRefGoogle Scholar
Partington, A., & Duguid, A. 2021. Political media discourses. In Friginal, E. & Hardy, J. (Eds.), The Routledge handbook of corpus approaches to discourse analysis (pp. 116–135). New York: Routledge.Google Scholar
Partington, A., Duguid, A., & Taylor, C. 2013. Patterns and meanings in discourse: Theory and practice in corpus-assisted discourse studies. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Partington, A., & Taylor, C. 2018. The language of persuasion in politics. London: Routledge.Google Scholar
Pennebaker, J. W., & Stone, L. D. 2003. Words of wisdom: Language use over the life span. Journal of Personality and Social Psychology, 85, 293–301.CrossRefGoogle ScholarPubMed
Sinclair, J. 2004. Trust the text: Language, corpus and discourse. London: Routledge.CrossRefGoogle Scholar
Singh, S. & Luthra, R. 2019. Savvy: Navigating fake companies, fake leaders and fake news in the post-trust era. Kindle Edition. Ideapress Publishing.Google Scholar
Taylor, C. 2010. Science in the news: A diachronic perspective. Corpora, 5(2), 221–250.CrossRefGoogle Scholar
Taylor, C. 2014. Investigating the representation of migrants in the UK and Italian press: A cross-linguistic corpus-assisted discourse analysis. International Journal of Corpus Linguistics, 19(3), 368–400.CrossRefGoogle Scholar
Taylor, C. 2018. Similarity. In Taylor, C. & Marchi, A. (Eds.), Corpus approaches to discourse: A critical review (pp. 19–37). London: Routledge.CrossRefGoogle Scholar
Taylor, C., & Marchi, A. (Eds.) 2018. Corpus approaches to discourse: A critical review. London: Routledge.Google Scholar
Thompson, M. 2016. Enough said: What’s gone wrong with the language of politics? London: Bodley Head.Google Scholar
Trump, D. 2015. Crippled America: How to make America great again. New York: Threshold.Google Scholar
Watts, R., Ide, S., & Ehlich, K. (Eds.) 1992. Politeness in language: Studies in its history, theory and practice. Berlin: Mouton de Gruyter.CrossRefGoogle Scholar
Zuccato, M., & Partington, A. 2018. Brexit: Before and after. A corpus-assisted study of the referendum campaigns and the immediate aftermath. Textus, 31(1), 119–140.Google Scholar
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