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Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS)ORCID iD: 0000-0002-1907-7820
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Potsdam University, Germany. (ISOVIS)ORCID iD: 0000-0001-6164-7762
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS)ORCID iD: 0000-0002-0519-2537
2018 (English)In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18) / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 102-103Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The analysis of various opinions and arguments in textual data can be facilitated by automatic topic modeling methods; however, the exploration and interpretation of the resulting topics and terms may prove to be difficult to the analysts. Opinions, stances, arguments, topics, terms, and text documents are usually connected with many-to-many relationships for such tasks. Exploratory visual analysis with interactive tools can help the analysts to get an overview of the topics and opinions, identify particularly interesting documents, and describe main themes of various arguments. In our previous work, we introduced an interactive tool called Topics2Themes that was used for topic and theme analysis of vaccination-related discussion texts with a limited set of stance categories. In this poster paper, we describe an application of Topics2Themes to a different genre of data, namely, political comments from Reddit, and multiple sentiment and stance categories detected with automatic classifiers.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018. p. 102-103
Keywords [en]
visualization, interaction, topic modeling, argument extraction, text visualization, sentiment analysis, sentiment visualization, stance analysis, stance visualization, annotation
National Category
Computer Sciences Language Technology (Computational Linguistics) Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-75856DOI: 10.1145/3231622.3232505Scopus ID: 2-s2.0-85055567433ISBN: 978-1-4503-6501-7 (electronic)OAI: oai:DiVA.org:lnu-75856DiVA, id: diva2:1217986
Conference
11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden
Funder
Swedish Research Council, 2016-06681Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2019-08-29Bibliographically approved

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Kucher, KostiantynSkeppstedt, MariaKerren, Andreas

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Citation style
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