Visual Analysis of Sentiment and Stance in Social Media Texts
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Despite the growing interest for visualization of sentiments and emotions in textual data, the task of detecting and visualizing various stances is not addressed well by the existing approaches. The challenges associated with this task include development of the underlying computational methods and visualization of the corresponding multi-label stance classification results. In this poster abstract, we describe the ongoing work on a visual analytics platform, called StanceVis Prime, which is designed for analysis of sentiment and stance in temporal text data from various social media data sources. Our approach consumes documents from several text stream sources, applies sentiment and stance classification, and provides end users with both an overview of the resulting data series and a detailed view for close reading and examination of the classifiers' output. The intended use case scenarios for StanceVis Prime include social media monitoring and research in sociolinguistics.
Description
@inproceedings{10.2312:eurp.20181127,
booktitle = {EuroVis 2018 - Posters},
editor = {Anna Puig and Renata Raidou},
title = {{Visual Analysis of Sentiment and Stance in Social Media Texts}},
author = {Kucher, Kostiantyn and Paradis, Carita and Kerren, Andreas},
year = {2018},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-065-9},
DOI = {10.2312/eurp.20181127}
}