DoSVis: Document stance visualization

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

Bibtex

@inproceedings{4ef5800c6c854d60bce6428458ade958,
title = "DoSVis: Document stance visualization",
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 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.",
keywords = "Information Visualization, Interaction, Sentiment Analysis, Sentiment Visualization, Stance Analysis, Stance Visualization, Text Analytics, Text Visualization",
author = "Kostiantyn Kucher and Carita Paradis and Andreas Kerren",
year = "2018",
month = jan,
day = "1",
language = "English",
volume = "3",
pages = "168--175",
booktitle = "Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",
publisher = "SciTePress",
note = "13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018 ; Conference date: 27-01-2018 Through 29-01-2018",

}