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Abstract
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.
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.
Original language | English |
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Pages | 56-57 |
Number of pages | 2 |
Publication status | Published - 2016 |
Event | International Symposium on Digital Humanities - Växjö City Library , Växjö, Sweden Duration: 2016 Nov 7 → 2016 Nov 8 https://lnu.se/en/research/conferences/international-digital-humanities-symposium |
Conference
Conference | International Symposium on Digital Humanities |
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Country/Territory | Sweden |
City | Växjö |
Period | 2016/11/07 → 2016/11/08 |
Internet address |
Subject classification (UKÄ)
- Specific Languages
- Engineering and Technology
Free keywords
- Digital humanities
- Stance
- Visualization
- interaction
- NLP
- Visual analytics
- Annotation
- Classifier training
Fingerprint
Dive into the research topics of 'Methodology and Applications of Visual Stance Analysis: An Interactive Demo'. Together they form a unique fingerprint.Projects
- 1 Finished
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StaViCTA - Advances in the description and explanation of stance in discourse using visual and computational text analytics
Paradis, C. (PI), Kerren, A. (PI), Sahlgren, M. (PI), Kucher, K. (Researcher), Skeppstedt, M. (Researcher) & Simaki, V. (PI)
2013/01/01 → 2018/01/02
Project: Research