Literature DB >> 30281459

A Task-Based Taxonomy of Cognitive Biases for Information Visualization.

Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, Pierre Dragicevic.   

Abstract

Information visualization designers strive to design data displays that allow for efficient exploration, analysis, and communication of patterns in data, leading to informed decisions. Unfortunately, human judgment and decision making are imperfect and often plagued by cognitive biases. There is limited empirical research documenting how these biases affect visual data analysis activities. Existing taxonomies are organized by cognitive theories that are hard to associate with visualization tasks. Based on a survey of the literature we propose a task-based taxonomy of 154 cognitive biases organized in 7 main categories. We hope the taxonomy will help visualization researchers relate their design to the corresponding possible biases, and lead to new research that detects and addresses biased judgment and decision making in data visualization.

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Year:  2018        PMID: 30281459     DOI: 10.1109/TVCG.2018.2872577

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  1 in total

1.  Impacts of Visualizations on Decoy Effects.

Authors:  Yuin Jeong; Sangheon Oh; Younah Kang; Sung-Hee Kim
Journal:  Int J Environ Res Public Health       Date:  2021-12-01       Impact factor: 3.390

  1 in total

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