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A survey on emotional visualization and visual analysis

Abstract

In the past 10 years, how to visualize human emotions in communication has become an important topic. For providing personalized customer service for enterprises from self-reflection in psychology to opinion mining, emotional visualization uses coded emotional computing results to make various basic charts, and some novel visual analysis systems for all-round analysis which intuitively reveal personal views and emotional styles. Emotion visualization uses coded emotion computing results to reflect the emotion analysis tasks, such as self-reflection in psychology or social media opinion mining results. With the help of various basic charts, infographics, and some novel visual analysis systems, it makes all directions’ analysis and intuitively reveals personal opinions and emotional styles. At present, emotional visualization has developed to use different platforms or multiple platforms to analyze various complex data, including text, sound, image, video, physiological signal or any mixed data. In this paper, we discuss a total of 75 approaches from four different categories: data source type, emotional computing, visual coding and visualization and visual analysis tasks, and 15 subcategories, including visual works mentioned in published paper and interactive visual works published on the Internet. Then, we discuss the further research approaches of emotional visualization and the prospects of emotional visualization under multidimensional data collaboration. We expect that this survey can help researchers interested in emotional visualization of varied data to find a more suitable visualization method for their data and projects.

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Wang, J., Gui, T., Cheng, M. et al. A survey on emotional visualization and visual analysis. J Vis (2022). https://doi.org/10.1007/s12650-022-00872-5

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Keywords

  • Emotional visualization
  • Affective visualization
  • Sentiment visualization
  • Visual analysis
  • Visual design