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Visual Analysis of Online Social Media to Open Up the Investigation of Stance Phenomena
Linnaeus University, Faculty of Technology, Department of Computer Science. (ISOVIS)ORCID iD: 0000-0002-1907-7820
Lund University. (ISOVIS)
Linnaeus University, Faculty of Technology, Department of Computer Science.ORCID iD: 0000-0002-0519-2537
Lund University.ORCID iD: 0000-0002-7240-9003
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2016 (English)In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 15, no 2, 93-116 p.Article in journal (Refereed) Published
Abstract [en]

Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.

Place, publisher, year, edition, pages
Sage Publications, 2016. Vol. 15, no 2, 93-116 p.
Keyword [en]
Visual analytics, visualization, text visualization, interaction, time-series, stance analysis, sentiment analysis, text analytics, visual linguistics, online social media, text and document data
National Category
Computer Science Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-41676DOI: 10.1177/1473871615575079ISI: 000371645100001Scopus ID: 2-s2.0-84964050221OAI: oai:DiVA.org:lnu-41676DiVA: diva2:800287
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2015-04-02 Created: 2015-04-02 Last updated: 2017-04-19Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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