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20182022
most citedTowards a Theory of Bullshit Visualization

2 citations · 4 across the 5 of their papers we have counts for

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cs.HC2022

Recommendations for Visualization Recommendations: Exploring Preferences and Priorities in Public Health

Calvin Bao, Siyao Li, Sarah Flores +2

The promise of visualization recommendation systems is that analysts will be automatically provided with relevant and high-quality visualizations that will reduce the work of manua…

cs.HC20211 cited

Illegible Semantics: Exploring the Design Space of Metal Logos

Gerrit J. Rijken, Rene Cutura, Frank Heyen +4

The logos of metal bands can be by turns gaudy, uncouth, or nearly illegible. Yet, these logos work: they communicate sophisticated notions of genre and emotional affect. In this p…

cs.HC2021

Untidy Data: The Unreasonable Effectiveness of Tables

Lyn Bartram, Michael Correll, Melanie Tory

Working with data in table form is usually considered a preparatory and tedious step in the sensemaking pipeline; a way of getting the data ready for more sophisticated visualizati…

cs.HC2021

User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics

Anamaria Crisan, Michael Correll

Topic models are widely used analysis techniques for clustering documents and surfacing thematic elements of text corpora. These models remain challenging to optimize and often req…

cs.HC20211 cited

Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations

Rachael Zehrung, Astha Singhal, Michael Correll +1

More visualization systems are simplifying the data analysis process by automatically suggesting relevant visualizations. However, little work has been done to understand if users…

cs.HC2020

What Do We Actually Learn from Evaluations in the "Heroic Era" of Visualization?

Michael Correll

We often point to the relative increase in the amount and sophistication of evaluations of visualization systems versus the earliest days of the field as evidence that we are matur…