Visual analysis of stance markers in online social media

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Standard

Visual analysis of stance markers in online social media. / Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus.

2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014. Piscataway, NJ : IEEE - Institute of Electrical and Electronics Engineers Inc., 2015. p. 259-260 7042519.

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Harvard

Kucher, K, Kerren, A, Paradis, C & Sahlgren, M 2015, Visual analysis of stance markers in online social media. in 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014., 7042519, IEEE - Institute of Electrical and Electronics Engineers Inc., Piscataway, NJ, pp. 259-260, 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014, Paris, France, 2014/11/09. https://doi.org/10.1109/VAST.2014.7042519

APA

Kucher, K., Kerren, A., Paradis, C., & Sahlgren, M. (2015). Visual analysis of stance markers in online social media. In 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014 (pp. 259-260). [7042519] IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VAST.2014.7042519

CBE

Kucher K, Kerren A, Paradis C, Sahlgren M. 2015. Visual analysis of stance markers in online social media. In 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014. Piscataway, NJ: IEEE - Institute of Electrical and Electronics Engineers Inc. pp. 259-260. https://doi.org/10.1109/VAST.2014.7042519

MLA

Kucher, Kostiantyn et al. "Visual analysis of stance markers in online social media". 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014. Piscataway, NJ: IEEE - Institute of Electrical and Electronics Engineers Inc. 2015, 259-260. https://doi.org/10.1109/VAST.2014.7042519

Vancouver

Kucher K, Kerren A, Paradis C, Sahlgren M. Visual analysis of stance markers in online social media. In 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014. Piscataway, NJ: IEEE - Institute of Electrical and Electronics Engineers Inc. 2015. p. 259-260. 7042519 https://doi.org/10.1109/VAST.2014.7042519

Author

Kucher, Kostiantyn ; Kerren, Andreas ; Paradis, Carita ; Sahlgren, Magnus. / Visual analysis of stance markers in online social media. 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014: Proceedings. Paris, France, 9-14 October 2014. Piscataway, NJ : IEEE - Institute of Electrical and Electronics Engineers Inc., 2015. pp. 259-260

RIS

TY - GEN

T1 - Visual analysis of stance markers in online social media

AU - Kucher, Kostiantyn

AU - Kerren, Andreas

AU - Paradis, Carita

AU - Sahlgren, Magnus

PY - 2015/2/13

Y1 - 2015/2/13

N2 - 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.

AB - 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.

KW - interaction

KW - NLP

KW - sentiment analysis

KW - stance analysis

KW - text analytics

KW - text visualization

KW - time-series

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=84929460615&partnerID=8YFLogxK

U2 - 10.1109/VAST.2014.7042519

DO - 10.1109/VAST.2014.7042519

M3 - Paper in conference proceeding

SN - 9781479962273

SP - 259

EP - 260

BT - 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway, NJ

T2 - 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014

Y2 - 9 November 2014 through 14 November 2014

ER -