Visual analysis of stance markers in online social media

Kostiantyn Kucher, Andreas Kerren, Carita Paradis, Magnus Sahlgren

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

4 Citations (SciVal)

Abstract

Stance in human communication is a linguistic concept relating to expressions of subjectivity such as the speakers' attitudes and emotions. Taking stance is crucial for the social construction of meaning and 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 results of computational linguistics techniques. Both aspects are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data and corresponding time-series that can be used to investigate stance phenomena and to refine the so-called stance markers collection.

Original languageEnglish
Title of host publication2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014
Subtitle of host publicationProceedings. Paris, France, 9-14 October 2014
Place of PublicationPiscataway, NJ
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages259-260
Number of pages2
ISBN (Print)9781479962273
DOIs
Publication statusPublished - 2015 Feb 13
Event2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - The Marriott Rive-Gauche, Paris, France
Duration: 2014 Nov 92014 Nov 14

Conference

Conference2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014
Country/TerritoryFrance
CityParis
Period2014/11/092014/11/14

Subject classification (UKÄ)

  • Languages and Literature
  • Media and Communications

Keywords

  • interaction
  • NLP
  • sentiment analysis
  • stance analysis
  • text analytics
  • text visualization
  • time-series
  • Visualization

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