Visual analysis of stance markers in online social media

Summary, in English

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.

• Author: Kostiantyn Kucher; Andreas Kerren; Carita Paradis; Magnus Sahlgren
• Department/s: English Studies; Language, Cognition and Discourse@Lund (LCD@L)
• Publishing year: 2015-02-13
• Language: English
• Pages: 259-260
• Publication/Series: 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 : Proceedings. Paris, France, 9-14 October 2014
• Links: http://dx.doi.org/10.1109/VAST.2014.7042519
• Document type: Conference paper
• Publisher: IEEE - Institute of Electrical and Electronics Engineers Inc.
• Topic: Languages and Literature; Media and Communications
• Keywords: interaction; NLP; sentiment analysis; stance analysis; text analytics; text visualization; time-series; Visualization
• Conference name: 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014
• Conference date: 2014-11-09 - 2014-11-14
• Conference place: Paris, France
• Status: Published
• Research group: Language, Cognition and Discourse@Lund (LCD@L)
• ISBN/ISSN/Other: ISBN: 9781479962273