Responsiveness: A Feature for Predicting the Productivity of Non-Convergent Discussions

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work focuses on estimating the impact of produced arguments on the discussion's upcoming development. We sought to define a feature upon which the productivity of non-convergent discussions can be predicted. We rely on the Bakhtinian notion of responsiveness, the degree to which a speaker embeds or builds on the arguments of an interlocutor. We demonstrate the potential of this feature, using a corpus of 10,000 threads extracted from Reddit's 'Change My View' forum. Utilizing Synthetic Minority Oversampling Technique, we experimented with several supervised machine learning algorithms, each of which drew on a different set of selected features. The performance of the obtained models was evaluated through repeated stratified 10-fold cross-validation. Our preliminary results are encouraging: responsiveness contributes to accurate prediction of discussion productivity.

Original languageAmerican English
Title of host publicationISLS Annual Meeting 2023
Subtitle of host publicationBuilding Knowledge and Sustaining our Community - 16th International Conference on Computer-Supported Collaborative Learning, CSCL 2023 - Proceedings
EditorsCrina Damsa, Marcela Borge, Elizabeth Koh, Marcelo Worsley
Pages197-200
Number of pages4
ISBN (Electronic)9781737330684
StatePublished - 2023
Event16th International Conference on Computer-Supported Collaborative Learning, CSCL 2023 - Montreal, Canada
Duration: 10 Jun 202315 Jun 2023

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume2023-June

Conference

Conference16th International Conference on Computer-Supported Collaborative Learning, CSCL 2023
Country/TerritoryCanada
CityMontreal
Period10/06/2315/06/23

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Education

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