Methodology and Applications of Visual Stance Analysis: An Interactive Demo

Research output: Contribution to conferencePoster

Standard

Methodology and Applications of Visual Stance Analysis : An Interactive Demo. / Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus.

2016. 56-57 Poster session presented at International Symposium on Digital Humanities, Växjö, Sweden.

Research output: Contribution to conferencePoster

Harvard

Kucher, K, Kerren, A, Paradis, C & Sahlgren, M 2016, 'Methodology and Applications of Visual Stance Analysis: An Interactive Demo', International Symposium on Digital Humanities, Växjö, Sweden, 2016/11/07 - 2016/11/08 pp. 56-57. <https://lnu.se/contentassets/60702fb657fe49539530eaa834fda8ef/abstracts-final.pdf#page=56>

APA

Kucher, K., Kerren, A., Paradis, C., & Sahlgren, M. (2016). Methodology and Applications of Visual Stance Analysis: An Interactive Demo. 56-57. Poster session presented at International Symposium on Digital Humanities, Växjö, Sweden. https://lnu.se/contentassets/60702fb657fe49539530eaa834fda8ef/abstracts-final.pdf#page=56

CBE

Kucher K, Kerren A, Paradis C, Sahlgren M. 2016. Methodology and Applications of Visual Stance Analysis: An Interactive Demo. Poster session presented at International Symposium on Digital Humanities, Växjö, Sweden.

MLA

Kucher, Kostiantyn et al. Methodology and Applications of Visual Stance Analysis: An Interactive Demo. International Symposium on Digital Humanities, 07 Nov 2016, Växjö, Sweden, Poster, 2016. 2 p.

Vancouver

Kucher K, Kerren A, Paradis C, Sahlgren M. Methodology and Applications of Visual Stance Analysis: An Interactive Demo. 2016. Poster session presented at International Symposium on Digital Humanities, Växjö, Sweden.

Author

Kucher, Kostiantyn ; Kerren, Andreas ; Paradis, Carita ; Sahlgren, Magnus. / Methodology and Applications of Visual Stance Analysis : An Interactive Demo. Poster session presented at International Symposium on Digital Humanities, Växjö, Sweden.2 p.

RIS

TY - CONF

T1 - Methodology and Applications of Visual Stance Analysis

T2 - International Symposium on Digital Humanities

AU - Kucher, Kostiantyn

AU - Kerren, Andreas

AU - Paradis, Carita

AU - Sahlgren, Magnus

PY - 2016

Y1 - 2016

N2 - Analysis of stance in textual data can reveal the attitudes of speakers, ranging from general agreement/disagreement with other speakers to fine-grained indications of wishes and emotions. The implementation of an automatic stance classifier and corresponding visualization techniques facilitates the analysis of human communication and social media texts. Furthermore, scholars in Digital Humanities could also benefit from such an approach by applying it for literature studies. For example, a researcher could explore the usage of such stance categories as certainty or prediction in a novel. Analysis of such abstract categories in longer texts would be complicated or even impossible with simpler tools such as regular expression search.Our research on automatic and visual stance analysis is concerned with multiple theoretical and practical challenges in linguistics, computational linguistics, and information visualization. In this interactive demo, we demonstrate our web-based visual analytics system called ALVA, which is designed to support the text data annotation and stance classifier training stages.

AB - Analysis of stance in textual data can reveal the attitudes of speakers, ranging from general agreement/disagreement with other speakers to fine-grained indications of wishes and emotions. The implementation of an automatic stance classifier and corresponding visualization techniques facilitates the analysis of human communication and social media texts. Furthermore, scholars in Digital Humanities could also benefit from such an approach by applying it for literature studies. For example, a researcher could explore the usage of such stance categories as certainty or prediction in a novel. Analysis of such abstract categories in longer texts would be complicated or even impossible with simpler tools such as regular expression search.Our research on automatic and visual stance analysis is concerned with multiple theoretical and practical challenges in linguistics, computational linguistics, and information visualization. In this interactive demo, we demonstrate our web-based visual analytics system called ALVA, which is designed to support the text data annotation and stance classifier training stages.

KW - Digital humanities

KW - Stance

KW - Visualization

KW - interaction

KW - NLP

KW - Visual analytics

KW - Annotation

KW - Classifier training

M3 - Poster

SP - 56

EP - 57

Y2 - 7 November 2016 through 8 November 2016

ER -