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Visual analysis of stance markers in online social media

Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita LU and Sahlgren, Magnus (2014) IEEE Visual Analytics Science and Technology (VAST '14),
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... (More)
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. (Less)
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author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
visualization, text visualization, interaction, time-series, stance analsyis, sentiment analysis, NLP, text analystics
conference name
IEEE Visual Analytics Science and Technology (VAST '14),
language
English
LU publication?
yes
id
5ff5701c-ae38-4ada-b492-f518069c992f (old id 4586851)
date added to LUP
2014-08-15 11:53:58
date last changed
2016-10-11 08:58:18
@misc{5ff5701c-ae38-4ada-b492-f518069c992f,
  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.},
  author       = {Kucher, Kostiantyn and Kerren, Andreas and Paradis, Carita and Sahlgren, Magnus},
  keyword      = {visualization,text visualization,interaction,time-series,stance analsyis,sentiment analysis,NLP,text analystics},
  language     = {eng},
  title        = {Visual analysis of stance markers in online social media},
  year         = {2014},
}