Visual Analysis of Sentiment and Stance in Social Media Texts

Research output: Contribution to conferencePoster

Standard

Visual Analysis of Sentiment and Stance in Social Media Texts. / Kucher, Kostiantyn; Paradis, Carita; Kerren, Andreas.

2018. Poster session presented at EuroVis 2018, Brno, Czech Republic.

Research output: Contribution to conferencePoster

Harvard

Kucher, K, Paradis, C & Kerren, A 2018, 'Visual Analysis of Sentiment and Stance in Social Media Texts', EuroVis 2018, Brno, Czech Republic, 2018/06/04 - 2018/06/08.

APA

Kucher, K., Paradis, C., & Kerren, A. (2018). Visual Analysis of Sentiment and Stance in Social Media Texts. Poster session presented at EuroVis 2018, Brno, Czech Republic.

CBE

Kucher K, Paradis C, Kerren A. 2018. Visual Analysis of Sentiment and Stance in Social Media Texts. Poster session presented at EuroVis 2018, Brno, Czech Republic.

MLA

Kucher, Kostiantyn, Carita Paradis and Andreas Kerren Visual Analysis of Sentiment and Stance in Social Media Texts. EuroVis 2018, 04 Jun 2018, Brno, Czech Republic, Poster, 2018.

Vancouver

Kucher K, Paradis C, Kerren A. Visual Analysis of Sentiment and Stance in Social Media Texts. 2018. Poster session presented at EuroVis 2018, Brno, Czech Republic.

Author

Kucher, Kostiantyn ; Paradis, Carita ; Kerren, Andreas. / Visual Analysis of Sentiment and Stance in Social Media Texts. Poster session presented at EuroVis 2018, Brno, Czech Republic.

RIS

TY - CONF

T1 - Visual Analysis of Sentiment and Stance in Social Media Texts

AU - Kucher, Kostiantyn

AU - Paradis, Carita

AU - Kerren, Andreas

N1 - Conference code: 20

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - visualization

KW - visual analytics

KW - text mining

KW - sentiment

KW - stance

KW - Natural language processing

M3 - Poster

T2 - EuroVis 2018

Y2 - 4 June 2018 through 8 June 2018

ER -