articleApr 10, 2010Closed access

Crowdsourcing graphical perception

Stanford University

Indexed incrossref

Abstract

Understanding perception is critical to effective visualization design. With its low cost and scalability, crowdsourcing presents an attractive option for evaluating the large design space of visualizations; however, it first requires validation. In this paper, we assess the viability of Amazon's Mechanical Turk as a platform for graphical perception experiments. We replicate previous studies of spatial encoding and luminance contrast and compare our results. We also conduct new experiments on rectangular area perception (as in treemaps or cartograms) and on chart size and gridline spacing. Our results demonstrate that crowdsourced perception experiments are viable and contribute new insights for visualization…

Citation impact

813
total citations
FWCI
45.84
Percentile
100%
References
37
Citations per year

Authors

2

Topics & keywords

Keywords
  • Crowdsourcing
  • Computer science
  • Perception
  • Graphical model
  • Data science
  • Human–computer interaction
  • Artificial intelligence
  • Psychology
No related works found for this paper.