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StanceXplore: Visualization for the Interactive Exploration of Stance in Social Media

Martins, Rafael, M. ; Simaki, Vasiliki LU ; Kucher, Kostiantyn ; Paradis, Carita LU and Kerren, Andreas (2017) 2nd Workshop on Visualization for the Digital Humanities
Abstract
The use of interactive visualization techniques in Digital Humanities research can be a useful addition when traditional automated machine learning techniques face difficulties, as is often the case with the exploration of large volumes of dynamic—and in many cases, noisy and conflicting—textual data from social media. Recently, the field of stance analysis has been moving from a predominantly binary approach—either pro or con—to a multifaceted one, where each unit of text may be classified as one (or more) of multiple possible stance categories. This change adds more layers of complexity to an already hard problem, but also opens up new opportunities for obtaining richer and more relevant results from the analysis of stance-taking in... (More)
The use of interactive visualization techniques in Digital Humanities research can be a useful addition when traditional automated machine learning techniques face difficulties, as is often the case with the exploration of large volumes of dynamic—and in many cases, noisy and conflicting—textual data from social media. Recently, the field of stance analysis has been moving from a predominantly binary approach—either pro or con—to a multifaceted one, where each unit of text may be classified as one (or more) of multiple possible stance categories. This change adds more layers of complexity to an already hard problem, but also opens up new opportunities for obtaining richer and more relevant results from the analysis of stance-taking in social media. In this paper we propose StanceXplore, a new visualization for the interactive exploration of stance in social media. Our goal is to offer DH researchers the chance to explore stance-classified text corpora from different perspectives at the same time, using coordinated multiple views including user-defined topics, content similarity and dissimilarity, and geographical and temporal distribution. As a case study, we explore the activity of Twitter users in Sweden, analyzing their behavior in terms of topics discussed and the stances taken. Each textual unit (tweet) is labeled with one of eleven stance categories from a cognitive-functional stance framework based on recent work. We illustrate how StanceXplore can be used effectively to investigate multidimensional patterns and trends in stance-taking related to cultural events, their geographical distribution, and the confidence of the stance classifier. (Less)
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author
; ; ; and
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
text mining, digital humanities, social media, machine learning
pages
5 pages
conference name
2nd Workshop on Visualization for the Digital Humanities<br/>
conference location
Phoenix, United States
conference dates
2017-10-02 - 2017-10-02
project
StaViCTA - Advances in the description and explanation of stance in discourse using visual and computational text analytics
language
English
LU publication?
yes
id
044aca97-ecdb-4769-81a3-f786492dc75b
date added to LUP
2018-03-29 10:03:19
date last changed
2019-11-26 03:12:09
@misc{044aca97-ecdb-4769-81a3-f786492dc75b,
  abstract     = {The use of interactive visualization techniques in Digital Humanities research can be a useful addition when traditional automated machine learning techniques face difficulties, as is often the case with the exploration of large volumes of dynamic—and in many cases, noisy and conflicting—textual data from social media. Recently, the field of stance analysis has been moving from a predominantly binary approach—either pro or con—to a multifaceted one, where each unit of text may be classified as one (or more) of multiple possible stance categories. This change adds more layers of complexity to an already hard problem, but also opens up new opportunities for obtaining richer and more relevant results from the analysis of stance-taking in social media.  In this paper we propose StanceXplore, a new visualization for the interactive exploration of stance in social media.  Our goal is to offer DH researchers the chance to explore stance-classified text corpora from different perspectives at the same time, using coordinated multiple views including user-defined topics, content similarity and dissimilarity, and geographical and temporal distribution. As a case study, we explore the activity of Twitter users in Sweden, analyzing their behavior in terms of topics discussed and the stances taken. Each textual unit (tweet) is labeled with one of eleven stance categories from a cognitive-functional stance framework based on recent work. We illustrate how StanceXplore can be used effectively to investigate multidimensional patterns and trends in stance-taking related to cultural events, their geographical distribution, and the confidence of the stance classifier.},
  author       = {Martins, Rafael, M. and Simaki, Vasiliki and Kucher, Kostiantyn and Paradis, Carita and Kerren, Andreas},
  language     = {eng},
  title        = {StanceXplore: Visualization for the Interactive Exploration of Stance in Social Media},
  url          = {https://lup.lub.lu.se/search/ws/files/40622801/martins_vis4dh17.pdf},
  year         = {2017},
}