This paper illustrates an application of grammatical tagging as a methodological tool for the investigation of small specialized corpora. A contrastive analysis was performed on two tagged corpora that represent genres used for the purpose of financial disclosure: spoken earnings presentations and written earnings releases. The analysis focused on two key features that could be studied systematically and comprehensively thanks to grammatical tagging: lexical density and evaluative adjectives. The results revealed interesting differences between the two corpora that appeared to be influenced by mode, interactional setting, and role/status of speakers and writers. The study shows how grammatical tagging offers new ways to integrate quantitative and qualitative methods in order to better understand discourse used in specific communicative contexts.

Using grammatical tagging to explore spoken/written variation in small specialized corpora

CRAWFORD, BELINDA BLANCHE
2013-01-01

Abstract

This paper illustrates an application of grammatical tagging as a methodological tool for the investigation of small specialized corpora. A contrastive analysis was performed on two tagged corpora that represent genres used for the purpose of financial disclosure: spoken earnings presentations and written earnings releases. The analysis focused on two key features that could be studied systematically and comprehensively thanks to grammatical tagging: lexical density and evaluative adjectives. The results revealed interesting differences between the two corpora that appeared to be influenced by mode, interactional setting, and role/status of speakers and writers. The study shows how grammatical tagging offers new ways to integrate quantitative and qualitative methods in order to better understand discourse used in specific communicative contexts.
2013
9789027210388
Corpus annotation
corpus linguistics
specialized discourse
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/344287
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