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DoSVis : Document stance visualization

Kucher, Kostiantyn ; Paradis, Carita LU orcid and Kerren, Andreas (2018) 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018 3. p.168-175
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Information Visualization, Interaction, Sentiment Analysis, Sentiment Visualization, Stance Analysis, Stance Visualization, Text Analytics, Text Visualization
host publication
Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
volume
3
pages
8 pages
publisher
SciTePress
conference name
13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018
conference location
Funchal, Madeira, Portugal
conference dates
2018-01-27 - 2018-01-29
external identifiers
  • scopus:85047909778
ISBN
9789897582899
language
English
LU publication?
yes
id
4ef5800c-6c85-4d60-bce6-428458ade958
date added to LUP
2018-06-15 13:57:01
date last changed
2021-09-22 03:28:21
@inproceedings{4ef5800c-6c85-4d60-bce6-428458ade958,
  abstract     = {<p>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.</p>},
  author       = {Kucher, Kostiantyn and Paradis, Carita and Kerren, Andreas},
  booktitle    = {Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications},
  isbn         = {9789897582899},
  language     = {eng},
  month        = {01},
  pages        = {168--175},
  publisher    = {SciTePress},
  title        = {DoSVis : Document stance visualization},
  volume       = {3},
  year         = {2018},
}