DoSVis: Document stance visualization

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

Standard

DoSVis : Document stance visualization. / Kucher, Kostiantyn; Paradis, Carita; Kerren, Andreas.

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Vol. 3 SciTePress, 2018. p. 168-175.

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

Harvard

Kucher, K, Paradis, C & Kerren, A 2018, DoSVis: Document stance visualization. in Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. vol. 3, SciTePress, pp. 168-175, 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, Funchal, Madeira, Portugal, 2018/01/27.

APA

Kucher, K., Paradis, C., & Kerren, A. (2018). DoSVis: Document stance visualization. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Vol. 3, pp. 168-175). SciTePress.

CBE

Kucher K, Paradis C, Kerren A. 2018. DoSVis: Document stance visualization. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SciTePress. pp. 168-175.

MLA

Kucher, Kostiantyn, Carita Paradis and Andreas Kerren "DoSVis: Document stance visualization". Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SciTePress. 2018, 168-175.

Vancouver

Kucher K, Paradis C, Kerren A. DoSVis: Document stance visualization. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Vol. 3. SciTePress. 2018. p. 168-175

Author

Kucher, Kostiantyn ; Paradis, Carita ; Kerren, Andreas. / DoSVis : Document stance visualization. Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Vol. 3 SciTePress, 2018. pp. 168-175

RIS

TY - GEN

T1 - DoSVis

T2 - 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018

AU - Kucher, Kostiantyn

AU - Paradis, Carita

AU - Kerren, Andreas

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer's attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature.

AB - Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer's attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature.

KW - Information Visualization

KW - Interaction

KW - Sentiment Analysis

KW - Sentiment Visualization

KW - Stance Analysis

KW - Stance Visualization

KW - Text Analytics

KW - Text Visualization

UR - http://www.scopus.com/inward/record.url?scp=85047909778&partnerID=8YFLogxK

M3 - Paper in conference proceeding

AN - SCOPUS:85047909778

VL - 3

SP - 168

EP - 175

BT - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

PB - SciTePress

Y2 - 27 January 2018 through 29 January 2018

ER -