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StanceXplore: Visualization for the Interactive Exploration of Stance in Social Media
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). (ISOVIS)ORCID-id: 0000-0002-2901-935X
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Lund University. (ISOVIS)ORCID-id: 0000-0002-8998-3618
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). (ISOVIS)ORCID-id: 0000-0002-1907-7820
Lund University.ORCID-id: 0000-0002-7240-9003
Vise andre og tillknytning
2017 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

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 stancetaking 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. 

sted, utgiver, år, opplag, sider
2017.
Emneord [en]
Stance Visualization, Sentiment Analysis, Digital Humanities, Visual Analytics, Social Media Text
HSV kategori
Forskningsprogram
Datavetenskap, Informations- och programvisualisering
Identifikatorer
URN: urn:nbn:se:lnu:diva-67320OAI: oai:DiVA.org:lnu-67320DiVA, id: diva2:1134669
Konferanse
2nd Workshop on Visualization for the Digital Humanities (VIS4DH '17) at IEEE VIS '17, October 2017, Phoenix, Arizona, USA
Prosjekter
StaViCTADISA-DH
Forskningsfinansiär
Swedish Research Council, 2012-5659Tilgjengelig fra: 2017-08-21 Laget: 2017-08-21 Sist oppdatert: 2019-04-08bibliografisk kontrollert

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Martins, Rafael MessiasSimaki, VasilikiKucher, KostiantynKerren, Andreas

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Martins, Rafael MessiasSimaki, VasilikiKucher, KostiantynParadis, CaritaKerren, Andreas
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