Visual analysis of online social media to open up the investigation of stance phenomena. (April 2016)
- Record Type:
- Journal Article
- Title:
- Visual analysis of online social media to open up the investigation of stance phenomena. (April 2016)
- Main Title:
- Visual analysis of online social media to open up the investigation of stance phenomena
- Authors:
- Kucher, Kostiantyn
Schamp-Bjerede, Teri
Kerren, Andreas
Paradis, Carita
Sahlgren, Magnus - Abstract:
- 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 byOnline 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. … (more)
- Is Part Of:
- Information visualization. Volume 15:Number 2(2016:Apr.)
- Journal:
- Information visualization
- Issue:
- Volume 15:Number 2(2016:Apr.)
- Issue Display:
- Volume 15, Issue 2 (2016)
- Year:
- 2016
- Volume:
- 15
- Issue:
- 2
- Issue Sort Value:
- 2016-0015-0002-0000
- Page Start:
- 93
- Page End:
- 116
- Publication Date:
- 2016-04
- Subjects:
- Visual analytics -- visualization -- text visualization -- interaction -- time-series -- stance analysis -- sentiment analysis -- text analytics -- visual linguistics -- online social media -- text and document data
Information visualization -- Periodicals
006.605 - Journal URLs:
- http://ivi.sagepub.com/ ↗
http://www.palgrave-journals.com/ivs/index.html ↗
http://www.uk.sagepub.com ↗ - DOI:
- 10.1177/1473871615575079 ↗
- Languages:
- English
- ISSNs:
- 1473-8716
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.401000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7844.xml