Unshared Task: (Dis)agreement in Online Debates

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

Topic-independent expressions for conveying agreement and disagreement were annotated in a corpus of web forum debates, in order to evaluate a classifier trained to detect these two categories. Among the 175 expressions annotated in the evaluation set, 163 were unique, which shows that there is large variation in expressions used. This variation might be one of the reasons why the task of automatically detecting the categories was difficult. F-scores of 0.44 and 0.37 were achieved by a classifier trained on 2,000 debate sentences for detecting sentence-level agreement and disagreement.

Details

Authors
Organisations
External organisations
  • Gagavai AB
  • Linnaeus University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Specific Languages
  • Engineering and Technology

Keywords

  • argumentation mining, online debates, classifier, agreement, disagreement, stance, corpus, annotation
Original languageEnglish
Title of host publicationThe 54th Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationProceedings of the 3rd Workshop on Argument Mining
PublisherAssociation for Computational Linguistics
Pages154-159
ISBN (Electronic)978-1-945626-17-3
Publication statusPublished - 2016
Publication categoryResearch
Peer-reviewedYes
Event3rd Workshop on Argument Mining (ArgMining '16) - Berlin, Germany
Duration: 2016 Aug 72016 Aug 12

Conference

Conference3rd Workshop on Argument Mining (ArgMining '16)
CountryGermany
CityBerlin
Period2016/08/072016/08/12