26 citations · 73 across the 24 of their papers we have counts for
24 papers
Visual Embellishments are Potential Distractions in Double-Column Reading
Songwen Hu, Chase Stokes, Marti Hearst +1
Eye-catching graphics, such as circular figure labels and word-scale visualizations, are increasingly being placed directly within long-form text paragraphs. Some research has clai…
How Data Narratives Go Wrong: A Taxonomy of Issues Across the Data Communication Process
Yu Fu, Jiawei Zhou, Sichen Jin +3
Data narratives increasingly shape public understanding, but their failures are rarely just isolated factual errors or deceptive charts. Instead, they emerge through a broader mean…
Data-Induced Groupings and How To Find Them
Yilan Jiang, Cindy Xiong Bearfield, Steven Franconeri +1
Making sense of a visualization requires the reader to consider both the visualization design and the underlying data values. Existing work in the visualization community has large…
MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces
Reuben A. Luera, Ryan Rossi, Franck Dernoncourt +12
In an ideal design pipeline, user interface (UI) design is intertwined with user research to validate decisions, yet studies are often resource-constrained during early exploration…
Playing telephone with generative models: "verification disability," "compelled reliance," and accessibility in data visualization
Frank Elavsky, Cindy Xiong Bearfield
This paper is a collaborative piece between two worlds of expertise in the field of data visualization: accessibility and bias. In particular, the rise of generative models playing…
Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models
Zhanna Kaufman, Madeline Endres, Cindy Xiong Bearfield +1
Systems relying on ML have become ubiquitous, but so has biased behavior within them. Research shows that bias significantly affects stakeholders' trust in systems and how they use…
Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attention
Minsuk Chang, Yao Wang, Huichen Will Wang +3
Accounting for individual differences can improve the effectiveness of visualization design. While the role of visual attention in visualization interpretation is well recognized,…
Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances
Chase Stokes, Kylie Lin, Cindy Xiong Bearfield
A growing body of work on visualization affordances highlights how specific design choices shape reader takeaways from information visualizations. However, mapping the relationship…
Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models
Aimen Gaba, Emily Wall, Tejas Ramkumar Babu +3
Large language models (LLMs) are becoming increasingly ubiquitous in our daily lives, but numerous concerns about bias in LLMs exist. This study examines how gender-diverse populat…
Perception-aware Sampling for Scatterplot Visualizations
Zafeiria Moumoulidou, Hamza Elhamdadi, Ke Yang +3
Visualizing data is often a crucial first step in data analytics workflows, but growing data sizes pose challenges due to computational and visual perception limitations. As a resu…
Do You "Trust" This Visualization? An Inventory to Measure Trust in Visualizations
Huichen Will Wang, Kylie Lin, Andrew Cohen +4
Trust plays a critical role in visual data communication and decision-making, yet existing visualization research employs varied trust measures, making it challenging to compare an…
Grid Labeling: Crowdsourcing Task-Specific Importance from Visualizations
Minsuk Chang, Yao Wang, Huichen Will Wang +2
Knowing where people look in visualizations is key to effective design. Yet, existing research primarily focuses on free-viewing-based saliency models - although visual attention i…
From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
Yixuan Li, Emery D. Berger, Minsuk Kahng +1
Visualization design influences how people perceive data patterns, yet most research focuses on low-level analytic tasks, such as finding correlations. The extent to which these pe…
How Aligned are Human Chart Takeaways and LLM Predictions? A Case Study on Bar Charts with Varying Layouts
Huichen Will Wang, Jane Hoffswell, Sao Myat Thazin Thane +2
Large Language Models (LLMs) have been adopted for a variety of visualizations tasks, but how far are we from perceptually aware LLMs that can predict human takeaways? Graphical pe…
Efficiently Crowdsourcing Visual Importance with Punch-Hole Annotation
Minsuk Chang, Soohyun Lee, Aeri Cho +4
We introduce a novel crowdsourcing method for identifying important areas in graphical images through punch-hole labeling. Traditional methods, such as gaze trackers and mouse-base…
Motion-based visual encoding can improve performance on perceptual tasks with dynamic time series
Songwen Hu, Ouxun Jiang, Jeffrey Riedmiller +1
Dynamic data visualizations can convey large amounts of information over time, such as using motion to depict changes in data values for multiple entities. Such dynamic displays pu…
Gridlines Mitigate Sine Illusion in Line Charts
Clayton Knittel, Jane Awuah, Steven Franconeri +1
Sine illusion happens when the more quickly changing pairs of lines lead to bigger underestimates of the delta between them. We evaluate three visual manipulations on mitigating si…
Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations
Cindy Xiong Bearfield, Lisanne van Weelden, Adam Waytz +1
People routinely rely on data to make decisions, but the process can be riddled with biases. We show that patterns in data might be noticed first or more strongly, depending on how…
The Role of Text in Visualizations: How Annotations Shape Perceptions of Bias and Influence Predictions
Chase Stokes, Cindy Xiong Bearfield, Marti A. Hearst
This paper investigates the role of text in visualizations, specifically the impact of text position, semantic content, and biased wording. Two empirical studies were conducted bas…
Attack-Resilient Image Watermarking Using Stable Diffusion
Lijun Zhang, Xiao Liu, Antoni Viros Martin +3
Watermarking images is critical for tracking image provenance and proving ownership. With the advent of generative models, such as stable diffusion, that can create fake but realis…
What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts
Cindy Xiong Bearfield, Chase Stokes, Andrew Lovett +1
Reading a visualization is like reading a paragraph. Each sentence is a comparison: the mean of these is higher than those; this difference is smaller than that. What determines wh…
Vistrust: a Multidimensional Framework and Empirical Study of Trust in Data Visualizations
Hamza Elhamdadi, Adam Stefkovics, Johanna Beyer +3
Trust is an essential aspect of data visualization, as it plays a crucial role in the interpretation and decision-making processes of users. While research in social sciences outli…
Polarizing Political Polls: How Visualization Design Choices Can Shape Public Opinion and Increase Political Polarization
Eli Holder, Cindy Xiong Bearfield
While we typically focus on data visualization as a tool for facilitating cognitive tasks (e.g., learning facts, making decisions), we know relatively little about their second-ord…
My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning
Aimen Gaba, Zhanna Kaufman, Jason Chueng +4
Machine learning technology has become ubiquitous, but, unfortunately, often exhibits bias. As a consequence, disparate stakeholders need to interact with and make informed decisio…