Managing the Complexity of Dialogues in Context: A Data-Driven Discovery Method for Dialectical Reply Structures
| Autor: | Olena Yaskorska-Shah |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Dialectic
Structure (mathematical logic) Linguistics and Language Computer science media_common.quotation_subject Dialogical self Context (language use) 0102 computer and information sciences 06 humanities and the arts 0603 philosophy ethics and religion 01 natural sciences Epistemology Argumentation theory Philosophy 010201 computation theory & mathematics 060302 philosophy Normative Natural (music) Function (engineering) media_common |
| Zdroj: | Argumentation. 35:551-580 |
| ISSN: | 1572-8374 0920-427X |
| DOI: | 10.1007/s10503-020-09543-x |
| Popis: | Current formal dialectical models postulate normative rules that enable discussants to conduct dialogical interactions without committing fallacies. Though the rules for conducting a dialogue are supposed to apply to interactions between actual arguers, they are without exception theoretically motivated. This creates a gap between model and reality, because dialogue participants typically leave important content-related elements implicit. Therefore, analysts cannot readily relate normative rules to actual debates in ways that will be empirically confirmable. This paper details a new, data-driven method for describing discussants’ actual reply structures, wherein corpus studies serve to acknowledge the complexity of natural argumentation (itself understood as a function of context). Rather than refer exclusively to propositional content as an indicator of arguing pro/contra a given claim, the proposed approach to dialogue structure tracks the sequence of dialogical moves itself. This arguably improves the applicability of theoretical dialectical models to empirical data, and thus advances the study of dialogue systems. |
| Databáze: | OpenAIRE |
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