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DoSVis: Document Stance Visualization
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-1907-7820
Lund University.ORCID iD: 0000-0002-7240-9003
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science. (ISOVIS, DISA-DH)ORCID iD: 0000-0002-0519-2537
2018 (English)In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18) / [ed] Alexandru C. Telea, Andreas Kerren, and José Braz, SciTePress, 2018, Vol. 3, p. 168-175Conference paper, Published paper (Refereed)
Abstract [en]

Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer’s attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature. 

Place, publisher, year, edition, pages
SciTePress, 2018. Vol. 3, p. 168-175
Keyword [en]
Stance Visualization, Sentiment Visualization, Text Visualization, Stance Analysis, Sentiment Analysis, Text Analytics, Information Visualization, Interaction
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-68428DOI: 10.5220/0006539101680175ISBN: 978-989-758-289-9 (print)OAI: oai:DiVA.org:lnu-68428DiVA, id: diva2:1151592
Conference
International Conference on Information Visualization Theory and Applications (IVAPP), Funchal-Madeira, Portugal, 27-29 January, 2018
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-04-12Bibliographically approved

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Kucher, KostiantynKerren, Andreas

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Citation style
  • apa
  • harvard1
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Language
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  • en-GB
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  • Other locale
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Output format
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