Priyam Mohanty and Aditya Parameswaran

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2022-125

May 14, 2022

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-125.pdf

Visualizations have been widely employed to convey important information regarding COVID-19 to the public, regarding cases, deaths, and intervention effectiveness. However, the way the general public reacts to these visualizations, given their preexisting biases and beliefs, is understudied. Specifically, for visualizations that highlight interventions, it is unclear if and how the visualizations help shape user understanding, and how, if any, they change user’s beliefs. Early on in the pandemic, we collected intervention information manually and developed a visualization interface, COVIDVIS, that overlaid intervention information on case and death counts as a case study. Employing an extended version of this interface as an exemplar intervention visualization, we conducted a user study to collect the priors and posteriors of participants' opinions of COVID-19 intervention effectiveness before and after interacting with such visualizations. Analysis of the participants' reactions to our visualizations allowed us to group participants into three distinct personas: COVID-Cautious, New Believers, and Skeptics. By gauging each group's level of institutional trust and societal (interpersonal) trust, we uncover trends that help explain how the role of each form of trust changes the way people interpret and react to COVID-19 visualizations. Our findings have ramifications for anyone developing visualizations that are part of the public eye.

Advisors: Aditya Parameswaran

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BibTeX citation:

@mastersthesis{Mohanty:EECS-2022-125,
    Author= {Mohanty, Priyam and Parameswaran, Aditya},
    Editor= {Salehi, Niloufar},
    Title= {A Case Study on COVID-19 Intervention Visualizations: The Role of Trust, Beliefs, and Interpretations},
    School= {EECS Department, University of California, Berkeley},
    Year= {2022},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-125.html},
    Number= {UCB/EECS-2022-125},
    Abstract= {Visualizations have been widely employed to convey important information regarding COVID-19 to the public, regarding cases, deaths, and intervention effectiveness. However, the way the general public reacts to these visualizations, given their preexisting biases and beliefs, is understudied. Specifically, for visualizations that highlight interventions, it is unclear if and how the visualizations help shape user understanding, and how, if any, they change user’s beliefs. Early on in the pandemic, we collected intervention information manually and developed a visualization interface, COVIDVIS, that overlaid intervention information on case and death counts as a case study. Employing an extended version of this interface as an exemplar intervention visualization, we conducted a user study to collect the priors and posteriors of participants' opinions of COVID-19 intervention effectiveness before and after interacting with such visualizations. Analysis of the participants' reactions to our visualizations allowed us to group participants into three distinct personas: COVID-Cautious, New Believers, and Skeptics. By gauging each group's level of institutional trust and societal (interpersonal) trust, we uncover trends that help explain how the role of each form of trust changes the way people interpret and react to COVID-19 visualizations. Our findings have ramifications for anyone developing visualizations that are part of the public eye.},
}

EndNote citation:

%0 Thesis
%A Mohanty, Priyam 
%A Parameswaran, Aditya 
%E Salehi, Niloufar 
%T A Case Study on COVID-19 Intervention Visualizations: The Role of Trust, Beliefs, and Interpretations
%I EECS Department, University of California, Berkeley
%D 2022
%8 May 14
%@ UCB/EECS-2022-125
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-125.html
%F Mohanty:EECS-2022-125