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Evaluation of the Comprehensiveness of Bar Charts with and without Stacking Functionality using Eye-Tracking

Published:07 March 2017Publication History

ABSTRACT

Bar charts are widely used to visualize core results of experiments in research papers or display statistics in news, media, and other reports. However, visualizations like bar charts are mostly manually designed, static presentations of data without the option of adaption to a user's needs. But so far, it is unknown whether interactivity improves the understanding of charts. In this work, we compare static with dynamic bar charts, which offer an interactive stacking option. We assess the efficiency, effectiveness, and satisfaction when answering questions regarding the content of a bar chart. An eye-tracker is used to measure the efficiency. We have conducted a between group experiment with 38 participants. While one group had to solve the aggregation tasks using stackable, i.e., interactive bar charts, the other group was limited to static visualizations. Even though new interactive features require familiarization, we found that the stacking feature significantly helps completing the tasks with respect to efficiency, effectiveness, and satisfaction for bar charts of varying complexity.

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      • Published in

        cover image ACM Conferences
        CHIIR '17: Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval
        March 2017
        454 pages
        ISBN:9781450346771
        DOI:10.1145/3020165
        • Conference Chairs:
        • Ragnar Nordlie,
        • Nils Pharo,
        • Program Chairs:
        • Luanne Freund,
        • Birger Larsen,
        • Dan Russel

        Copyright © 2017 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 March 2017

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        • short-paper

        Acceptance Rates

        CHIIR '17 Paper Acceptance Rate10of48submissions,21%Overall Acceptance Rate55of163submissions,34%

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