A comparative evaluation of techniques for time series visualizations of emotions

Julia Sheidin, Joel Lanir, Tsvi Kuflik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The growing availability of social media and other online information sources has increased interest in sentiment analysis to understand the emotional responses of users. Being able to visualize users' emotions could help stakeholders to better understand the underlying trends behind events or stories. Various techniques have been used to generate time series visualizations of emotions; however, there is neither a prevalent method nor any guidelines for the design of visualizations that depict emotions and their evolution over time. We report on a controlled user study that compared four common visualization techniques. User performance and preferences were measured under a formal task taxonomy, using Twitter data about real-world events. The results, although highly task-dependent, show both an overall performance advantage and a higher level of user preference for the line chart, and suggest that the radar chart, despite its popularity in the literature, may not be the best choice to depict such data.

Original languageAmerican English
Title of host publicationCHItaly 2019 - Proceedings of the 13th Biannual Conference of the Italian SIGCHI Chapter Designing the Next Interaction
ISBN (Electronic)9781450371902
DOIs
StatePublished - 23 Sep 2019
Event13th Biannual Conference of the Italian SIGCHI Chapter Designing the Next Interaction, CHItaly 2019 - Padua, Italy
Duration: 23 Sep 201925 Sep 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference13th Biannual Conference of the Italian SIGCHI Chapter Designing the Next Interaction, CHItaly 2019
Country/TerritoryItaly
CityPadua
Period23/09/1925/09/19

Keywords

  • Emotion detection
  • Evaluation
  • Plutchik wheel of emotions
  • Visualization techniques

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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