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Examining Interpretation Strategies for Multiple Forecast Visualizations with Two and Four Forecasts: Article No. 1153

  • Lace Padilla
  • , Racquel Fygenson
  • , Connor Wilson
  • , Kristi Potter
  • , Spencer Castro
  • Northeastern University
  • University of California Merced

Research output: Contribution to conferencePaper

Abstract

Multiple forecast visualizations (MFVs) present curated sets of forecasts to support decision-making under uncertainty. However, the research community knows little about how people interpret and integrate competing forecasts. In this study, we investigate the strategies individuals use when predicting hypothetical future events with MFVs across five visualization types (median, 95% CIs, standard deviation intervals, density plots, and hypothetical outcome plots) and multiple probability distributions in two preregistered experiments (n = 500 each). Analysis of 18 participant strategies and open responses shows that whereas many participants attempted to visually average across forecasts, others adopted a winner-takes-all approach (e.g., selecting a single forecast as the most likely outcome), which deviates from rational agent expectations. We also observed reliance on visual artifacts, such as intersection points or end caps. These findings underscore the complexity of interpreting a range of forecasts and help explain why individuals may privilege particular predictions in real-world decision contexts.
Original languageAmerican English
Number of pages19
DOIs
StatePublished - 2026
Event2026 CHI Conference on Human Factors in Computing Systems - Barcelona, Spain
Duration: 14 Apr 202617 Apr 2026

Conference

Conference2026 CHI Conference on Human Factors in Computing Systems
CityBarcelona, Spain
Period14/04/2617/04/26

NLR Publication Number

  • NLR/CP-2C00-100897

Keywords

  • density plots
  • distributions
  • hypothetical outcome plots
  • multiple forecast visualization
  • uncertainty

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