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Visual Analysis of Text Annotations for Stance Classification with ALVA
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-1907-7820
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-0519-2537
Lund University .ORCID iD: 0000-0002-7240-9003
Gavagai AB.
2016 (English)In: EuroVis Posters 2016 / [ed] Tobias Isenberg & Filip Sadlo, Eurographics - European Association for Computer Graphics, 2016, p. 49-51Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The automatic detection and classification of stance taking in text data using natural language processing and machine learning methods create an opportunity to gain insight about the writers’ feelings and attitudes towards their own and other people’s utterances. However, this task presents multiple challenges related to the training data collection as well as the actual classifier training. In order to facilitate the process of training a stance classifier, we propose a visual analytics approach called ALVA for text data annotation and visualization. Our approach supports the annotation process management and supplies annotators with a clean user interface for labeling utterances with several stance categories. The analysts are provided with a visualization of stance annotations which facilitates the analysis of categories used by the annotators. ALVA is already being used by our domain experts in linguistics and computational linguistics in order to improve the understanding of stance phenomena and to build a stance classifier for applications such as social media monitoring. 

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2016. p. 49-51
Keywords [en]
Visualization, Text visualization, Interaction, Text annotations, Stance analysis, NLP, Text analytics
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization; Computer and Information Sciences Computer Science, Computer Science; Humanities, Linguistics
Identifiers
URN: urn:nbn:se:lnu:diva-52287DOI: 10.2312/eurp.20161139ISBN: 9783038680154 (print)OAI: oai:DiVA.org:lnu-52287DiVA, id: diva2:924290
Conference
The 18th EG/VGTC Conference on Visualization (EuroVis '16), Groningen, The Netherlands, 6-10 June,2016
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659Available from: 2016-04-28 Created: 2016-04-28 Last updated: 2018-01-10Bibliographically approved

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Kucher, KostiantynKerren, AndreasParadis, Carita

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
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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