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Big Data & Society
Article . 2022 . Peer-reviewed
License: CC BY NC
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Big Data & Society
Article . 2022
Data sources: DOAJ
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Anthropographics in COVID-19 simulations

Authors: Madeleine Sorapure;

Anthropographics in COVID-19 simulations

Abstract

Data visualization researchers and designers have explored a range of approaches to ensure that non-expert audiences understand and derive value from their work. Using anthropomorphized data graphics—or anthropographics—is one strategy that can help create a connection between data and audiences. Anthropographics have been defined as “visualizations that represent data about people in a way that is intended to promote prosocial feelings (e.g. compassion or empathy) or prosocial behavior (e.g. donating or helping).” However, during the SARS-CoV-2 pandemic, anthropographics were used in data visualizations that had an expanded range of rhetorical goals beyond promoting prosocial feelings and behavior—for instance, informing people about the pandemic, persuading them to adopt certain behaviors, or memorializing those killed by the virus. In particular, anthropographics were used in visualized simulations to model possible futures for audiences, showing the spread and impact of the virus in various scenarios. These simulations used anthropomorphizing strategies in text as well as in graphics, along with interactive options that enabled audiences to explore personal connections with the data. As demonstrated through a close reading of several of these COVID-19 simulations, anthropographics can be viewed holistically as a design strategy that incorporates text and interactivity as well as graphical marks in representing data. Findings from this analysis suggest several additions to the design space for anthropographics.

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    popularity
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold