Annotating Line Charts for Addressing Deception

Fan，Arlen1; Ma，Yuxin1,2; Mancenido，Michelle1; MacIejewski，Ross1

10.1145/3491102.3502138

2022-04-29

CHI Conference on Human Factors in Computing Systems (CHI)

Conference on Human Factors in Computing Systems - Proceedings

APR 30-MAY 05, 2022

null,New Orleans,LA

1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES

ASSOC COMPUTING MACHINERY

Deceptive visualizations are visualizations that, whether intentionally or not, lead the reader to an understanding of the data which varies from the actual data. Examples of deceptive visualizations can be found in every digital platform, and, despite their widespread use in the wild, there have been limited efforts to alert laypersons to common deceptive visualization practices. In this paper, we present a tool for annotating line charts in the wild that reads line chart images and outputs text and visual annotations to assess the line charts for distortions and help guide the reader towards an honest understanding of the chart data. We demonstrate the usefulness of our tool through a series of case studies on real-world charts. Finally, we perform a crowdsourced experiment to evaluate the ability of the proposed tool to educate readers about potentially deceptive visualization practices.

deceptive visualization educational tools visual literacy

通讯

英语

EI ; CPCI-S

U.S. Department of Homeland Security[17STQAC00001-02-00]

Computer Science ; Robotics

Computer Science, Information Systems ; Computer Science, Theory & Methods ; Robotics

WOS:000890212505017

20222112159009

Data visualization

Data Processing and Image Processing:723.2 ; Computer Applications:723.5

2-s2.0-85130531018

Scopus

1.Arizona State University,Tempe,United States
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China

Fan，Arlen,Ma，Yuxin,Mancenido，Michelle,et al. Annotating Line Charts for Addressing Deception[C]. 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES:ASSOC COMPUTING MACHINERY,2022.