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Active Learning for Detection of Stance Components
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0001-6164-7762
Swedish Institute of Computer Science.
Lund University.ORCID iD: 0000-0002-7240-9003
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-0519-2537
2016 (English)In: Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES '16) at COLING '16, Association for Computational Linguistics, 2016, 50-59 p.Conference paper, Published paper (Refereed)
Abstract [en]

Automatic detection of five language components, which are all relevant for expressing opinions and for stance taking, was studied: positive sentiment, negative sentiment, speculation, contrast and condition. A resource-aware approach was taken, which included manual annotation of 500 training samples and the use of limited lexical resources. Active learning was compared to random selection of training data, as well as to a lexicon-based method. Active learning was successful for the categories speculation, contrast and condition, but not for the two sentiment categories, for which results achieved when using active learning were similar to those achieved when applying a random selection of training data. This difference is likely due to a larger variation in how sentiment is expressed than in how speakers express the other three categories. This larger variation was also shown by the lower recall results achieved by the lexicon-based approach for sentiment than for the categories speculation, contrast and condition. 

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2016. 50-59 p.
Keyword [en]
active learning, stance, sentiment, annotation, classifier
National Category
Language Technology (Computational Linguistics)
Research subject
Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-57761ISBN: 978-4-87974-723-5 (print)OAI: oai:DiVA.org:lnu-57761DiVA: diva2:1044049
Conference
Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES '16), Osaka, Japan, December 12, 2016
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2016-11-01 Created: 2016-11-01 Last updated: 2017-04-19Bibliographically approved

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Skeppstedt, MariaParadis, CaritaKerren, Andreas
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf