%0 Conference Proceedings
%T A Formative Study of Interactive Bias Metrics in Visual Analytics Using Anchoring Bias
%+ Georgia Institute of Technology [Atlanta]
%+ Air Force Research Laboratory (AFRL)
%+ U.S. Department of Defense
%A Wall, Emily
%A Blaha, Leslie
%A Paul, Celeste
%A Endert, Alex
%Z Part 7: Information Visualization
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 17th IFIP Conference on Human-Computer Interaction (INTERACT)
%C Paphos, Cyprus
%Y David Lamas
%Y Fernando Loizides
%Y Lennart Nacke
%Y Helen Petrie
%Y Marco Winckler
%Y Panayiotis Zaphiris
%I Springer International Publishing
%3 Human-Computer Interaction – INTERACT 2019
%V LNCS-11747
%N Part II
%P 555-575
%8 2019-09-02
%D 2019
%R 10.1007/978-3-030-29384-0_34
%K Cognitive bias
%K Anchoring bias
%K Visual analytics
%Z Computer Science [cs]Conference papers
%X Interaction is the cornerstone of how people perform tasks and gain insight in visual analytics. However, people’s inherent cognitive biases impact their behavior and decision making during their interactive visual analytic process. Understanding how bias impacts the visual analytic process, how it can be measured, and how its negative effects can be mitigated is a complex problem space. Nonetheless, recent work has begun to approach this problem by proposing theoretical computational metrics that are applied to user interaction sequences to measure bias in real-time. In this paper, we implement and apply these computational metrics in the context of anchoring bias. We present the results of a formative study examining how the metrics can capture anchoring bias in real-time during a visual analytic task. We present lessons learned in the form of considerations for applying the metrics in a visual analytic tool. Our findings suggest that these computational metrics are a promising approach for characterizing bias in users’ interactive behaviors.
%G English
%Z TC 13
%2 https://inria.hal.science/hal-02544609/document
%2 https://inria.hal.science/hal-02544609/file/488591_1_En_34_Chapter.pdf
%L hal-02544609
%U https://inria.hal.science/hal-02544609
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC13
%~ IFIP-INTERACT
%~ IFIP-LNCS-11747