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Discourse Analysis and ANLP

Discourse Analysis and ANLP

Alexandra Kent, Philip M. McCarthy
Copyright: © 2012 |Pages: 20
ISBN13: 9781609607418|ISBN10: 1609607414|EISBN13: 9781609607425
DOI: 10.4018/978-1-60960-741-8.ch003
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MLA

Kent, Alexandra, and Philip M. McCarthy. "Discourse Analysis and ANLP." Applied Natural Language Processing: Identification, Investigation and Resolution, edited by Philip M. McCarthy and Chutima Boonthum-Denecke, IGI Global, 2012, pp. 33-52. https://doi.org/10.4018/978-1-60960-741-8.ch003

APA

Kent, A. & McCarthy, P. M. (2012). Discourse Analysis and ANLP. In P. McCarthy & C. Boonthum-Denecke (Eds.), Applied Natural Language Processing: Identification, Investigation and Resolution (pp. 33-52). IGI Global. https://doi.org/10.4018/978-1-60960-741-8.ch003

Chicago

Kent, Alexandra, and Philip M. McCarthy. "Discourse Analysis and ANLP." In Applied Natural Language Processing: Identification, Investigation and Resolution, edited by Philip M. McCarthy and Chutima Boonthum-Denecke, 33-52. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-60960-741-8.ch003

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Abstract

The goal of this chapter is to outline a (primarily) qualitative and (secondarily) quantitative approach to the analysis of discourse. Discourse Analysis thrives on the variation and inconsistencies in our everyday language. Rather than focusing on what is said and seeking to reduce and homogenise accounts to find a central meaning, discourse analysis is interested in the consequences of “saying it that particular way at that particular time.” Put another way, it is interested in “what was said that didn’t have to be, and why?” and “what wasn’t said that could have been, and why not?” The chapter outlines the basic theoretical assumptions that underpin the many different methodological approaches within Discourse Analysis. It then considers these approaches in terms of the major themes of their research, the ongoing and future directions for study, and the scope of contribution to scientific knowledge that discourse analytic research can make. At the beginning and end of the chapter, we attempt to outline a role for Applied Natural Language Processing (ANLP) in Discourse Analysis. We discuss possible reasons for a lack of computational tools and techniques in traditional Discourse Analysis but we also offer suggestions as to the application of computational resources so that researchers in both disciplines might have an avenue of interest that assists their work, without directing it.

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