The effect of user characteristics in time series visualizations

Julia Sheidin, Joel Lanir, Cristina Conati, Dereck Toker, Tsvi Kuflik

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


There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be enriched with personalization mechanisms that better fit each user's specific needs and abilities. In this paper, we contribute to this body of work with a study that investigates the impact of six user characteristics on the effectiveness of time series visualizations, which was not previously investigated in relation to personalizing Information visualization. We report on a controlled user study that compare four possible time series visualization techniques. User performance and how it was affected by user characteristics was measured while performing tasks from a formal taxonomy using Twitter data about real-world events. Our results show that both the personality trait of locus of control and the cognitive ability of verbal working memory influence which visualization is more effective when dealing with demanding and complex tasks. These findings extend the need for personalization to visualizations for time series data, and we discuss them in the context of creating systems that can utilize knowledge of the user's specific characteristics in order to present the most suitable visualization for each user.

Original languageEnglish
Title of host publicationProceedings of the 25th International Conference on Intelligent User Interfaces, IUI 2020
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450371186
StatePublished - 17 Mar 2020
Event25th ACM International Conference on Intelligent User Interfaces, IUI 2020 - Cagliari, Italy
Duration: 17 Mar 202020 Mar 2020

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI


Conference25th ACM International Conference on Intelligent User Interfaces, IUI 2020

Bibliographical note

Publisher Copyright:
© ACM.


  • adaptive information visualization
  • user characteristics
  • user evaluation

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction


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