Date of Award
Spring 4-25-2022
Degree Name
Master of Science (MS)
Degree Type
Thesis
Abstract
Data visualizations are increasingly accessible to people online, often to non-specialized audiences. However, what we know about how people make sense of data and engage with the visualized content is typically limited to observations from controlled user studies, sometimes with highly-specialized participants. As a result, there is a limited vocabulary to describe how visualizations as a technique of information sharing permeate organic communities. This thesis investigates how data visualization systems infiltrate online social settings and characterizes the conditions under which users engage or do not engage with them. We captured conversations on Reddit from March 2, 2021 to December 31, 2021, collecting 993,018 discussion threads. We found that data visualizations constituted 0.0002% (217 out of 993,018) of all threads cataloged, with all visualizations originating from one of four news sources: The Washington Post, The New York Times, The Guardian, or CNN. Our analysis suggests that visual design did not impact discourse or popularity. Rather, our findings spotlight that visualizations are often part of a broader information ecosystem, and the visual features may have no measurable impact on long-term engagement.
Language
English (en)
Chair
Professor Alvitta Ottley
Committee Members
Alvitta Ottley Caitlin Kelleher Ian Bogost