2017/10/01 by Isaac Cho, Ryan Wesslen, Alireza Karduni +3 · 1 citation
Computer Science · Psychology · #Advanced Text Analysis Techniques #Analytics #Anchoring #Artificial intelligence #Categorical variable #Cognitive science #Computer science #Data Analysis with R #Data Visualization and Analytics #Data science #Heuristics #Human–computer interaction #Machine learning #Psychology #Visual analytics #Visualization
paper · doi:10.1109/vast.2017.8585665
openalex publication_date 2017/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
Anchoring effect is the tendency to focus too heavily on one piece of information when making decisions. In this paper, we present a novel, systematic study and resulting analyses that investigate the effects of anchoring effect on human decision-making using visual analytic systems. Visual analytics interfaces typically contain multiple views that present various aspects of information such as spatial, temporal, and categorical. These views are designed to present complex, heterogeneous data in accessible forms that aid decision-making. However, human decision-making is often hindered by the use of heuristics, or cognitive biases, such as anchoring effect. Anchoring effect can be triggered by the order in which information is presented or the magnitude of information presented. Through carefully designed laboratory experiments, we present evidence of anchoring effect in analysis with visual analytics interfaces when users are primed by representation of different pieces of information. We also describe detailed analyses of users’ interaction logs which reveal the impact of anchoring bias on the visual representation preferred and paths of analysis. We discuss implications for future research to possibly detect and alleviate anchoring bias.