Visual Analysis of Sentiment and Stance in Social Media Texts

dc.contributor.authorKucher, Kostiantynen_US
dc.contributor.authorParadis, Caritaen_US
dc.contributor.authorKerren, Andreasen_US
dc.contributor.editorAnna Puig and Renata Raidouen_US
dc.date.accessioned2018-06-02T17:55:52Z
dc.date.available2018-06-02T17:55:52Z
dc.date.issued2018
dc.description.abstractDespite 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.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEuroVis 2018 - Posters
dc.identifier.doi10.2312/eurp.20181127
dc.identifier.isbn978-3-03868-065-9
dc.identifier.pages49-51
dc.identifier.urihttps://doi.org/10.2312/eurp.20181127
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurp20181127
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisual analytics
dc.subjectComputing methodologies
dc.subjectDiscourse
dc.subjectdialogue and pragmatics
dc.subjectInformation systems
dc.subjectSentiment analysis
dc.titleVisual Analysis of Sentiment and Stance in Social Media Textsen_US
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