Investigating genre distinctions through discourse distance and discourse network.

RST relation dependency representations discourse network genre differences linear distance

Journal

Corpus linguistics and linguistic theory
ISSN: 1613-7035
Titre abrégé: Corpus Linguist Linguist Theory
Pays: Germany
ID NLM: 9918471179406676

Informations de publication

Date de publication:
Nov 2021
Historique:
received: 12 02 2020
accepted: 05 02 2021
medline: 25 2 2021
entrez: 10 4 2023
pubmed: 25 2 2021
Statut: epublish

Résumé

The notion of genre has been widely explored using quantitative methods from both lexical and syntactical perspectives. However, discourse structure has rarely been used to examine genre. Mostly concerned with the interrelation of discourse units, discourse structure can play a crucial role in genre analysis. Nevertheless, few quantitative studies have explored genre distinctions from a discourse structure perspective. Here, we use two English discourse corpora (RST-DT and GUM) to investigate discourse structure from a novel viewpoint. The RST-DT is divided into four small subcorpora distinguished according to genre, and another corpus (GUM) containing seven genres are used for cross-verification. An RST (rhetorical structure theory) tree is converted into dependency representations by taking information from RST annotations to calculate the

Identifiants

pubmed: 37034897
doi: 10.1515/cllt-2020-0064
pii: cllt-2020-0064
pmc: PMC10076151
doi:

Types de publication

Journal Article

Langues

eng

Pagination

599-624

Informations de copyright

© 2021 Walter de Gruyter GmbH, Berlin/Boston.

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Auteurs

Kun Sun (K)

Department of Linguistics, University of Tübingen, Tübingen, Germany.

Rong Wang (R)

Institute of Computational Linguistics, University of Stuttgart, Stuttgart, Germany.
School of Foreign Languages, Hangzhou Dianzi University, Hangzhou, China.

Wenxin Xiong (W)

School of International Chinese Studies, Beijing Foreign Studies University, Beijing, China.

Classifications MeSH