Location
University of Windsor
Document Type
Paper
Keywords
argumentation, argument ontology, collective intelligence, computational tools for argument support, computer supported argument visualization, disagreement space, epistemic capabilities, natural language processing, sentiment identification
Start Date
22-5-2013 9:00 AM
End Date
25-5-2013 5:00 PM
Abstract
Natural language processing (NLP) research and design that aims to model and detect opposition in text for the purpose of opinion classification, sentiment analysis, and meeting tracking, generally excludes the interactional, pragmatic aspects of online text. We propose that a promising direction for NLP is to incorporate the insights of pragmatic, dialectical theories of argumentation to more fully exploit the potential of NLP to offer sound, robust systems for various kinds of argumentation support.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Response to Submission
Reader's Reactions
Sally Jackson, Commentary on: Mark Aakhus, Smaranda Muresan and Nina Wacholder's "Integrating natural language processing and pragmatic argumentation theories for argumentation support" (May 2013)
Included in
Integrating natural language processing and pragmatic argumentation theories for argumentation support
University of Windsor
Natural language processing (NLP) research and design that aims to model and detect opposition in text for the purpose of opinion classification, sentiment analysis, and meeting tracking, generally excludes the interactional, pragmatic aspects of online text. We propose that a promising direction for NLP is to incorporate the insights of pragmatic, dialectical theories of argumentation to more fully exploit the potential of NLP to offer sound, robust systems for various kinds of argumentation support.