The state of the art in sentiment visualization

Research output: Contribution to journalArticle

Abstract

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.

Details

Authors
Organisations
External organisations
  • Linnaeus University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Language Technology (Computational Linguistics)

Keywords

  • sentiment visualization, text visualization, sentiment analysis, opinion mining
Original languageEnglish
Pages (from-to)71-96
JournalComputer Graphics Forum
Volume37
Issue number1
Early online date2017 Jun 12
Publication statusPublished - 2018
Publication categoryResearch
Peer-reviewedYes

Related projects

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Swedish Research Council

2013/01/012018/01/02

Project: Research

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