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Investigating genre distinctions through discourse distance and discourse network.
Kun Sun1, Rong Wang2,3, Wenxin Xiong4
1Department of Linguistics, University of Tübingen, Tübingen, Germany.
Corpus Linguistics and Linguistic Theory
|April 10, 2023
Summary
This study introduces a novel quantitative method for genre analysis using discourse structure. By analyzing discourse distance and networks, it effectively distinguishes between different genres, enhancing our understanding of textual variety.
Area of Science:
- Computational Linguistics
- Discourse Analysis
- Genre Studies
Background:
- Quantitative genre analysis traditionally focuses on lexical and syntactical features.
- Discourse structure, crucial for interrelation of discourse units, has been underutilized in quantitative genre studies.
Purpose of the Study:
- To investigate genre distinctions using discourse structure from a novel quantitative perspective.
- To propose and validate an effective quantitative method for assessing genre differences.
Main Methods:
- Utilized two English discourse corpora (RST-DT and GUM) with multiple genres.
- Converted Rhetorical Structure Theory (RST) trees into dependency representations to calculate discourse distance.
- Transformed dependency data into network data for combined analysis.
Main Results:
- Demonstrated that discourse distance and discourse network analysis are complementary in revealing genre distinctiveness.
- Successfully applied the novel quantitative method to differentiate between genres across corpora.
Conclusions:
- Discourse structure analysis offers a powerful quantitative approach to genre differentiation.
- The proposed method of combining discourse distance and network analysis effectively assesses genre differences, advancing genre studies.
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