The State of the Art in Sentiment Visualization

Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualizatio...

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Veröffentlicht in:Computer graphics forum Jg. 37; H. 1; S. 71 - 96
Hauptverfasser: Kucher, Kostiantyn, Paradis, Carita, Kerren, Andreas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 2018
Schlagworte:
Analytics
Classification
Computer and Information Sciences
Data mining
Data- och informationsvetenskap (Datateknik)
Information and software visualization
Information systems → Sentiment analysis; • Human‐centred computing → Visualization techniques; • Human‐centred computing → Visual analytics; • Human‐centred computing → Information visualization; • Human‐centred computing → Visualization systems and tools
Informations- och programvisualisering
Multidimensional data
Natural Language Processing
Natural Sciences
Naturvetenskap
Online analytical processing
opinion mining
Researchers
Sentiment analysis
sentiment visualization
Språkbehandling och datorlingvistik
text visualization
Visualization
ISSN:0167-7055, 1467-8659, 1467-8659
Online-Zugang:Volltext
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Zusammenfassung:Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, including temporal, relational and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer‐reviewed publications together with an interactive web‐based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization. We expect this survey to be useful for visualization researchers whose interests include sentiment or other aspects of text data as well as researchers and practitioners from other disciplines in search of efficient visualization techniques applicable to their tasks and data. Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, including temporal, relational and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer‐reviewed publications together with an interactive web‐based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0167-7055
1467-8659
1467-8659
DOI:10.1111/cgf.13217