37 citations · 81 across the 17 of their papers we have counts for
19 papers
Quick-View Takeaways: How Does Title Framing Influences Pattern Identification in Line Charts?
Jasmine Lim, Tapendra Pandey, Arran Zeyu Wang +1
Visual data communication in digital media is increasingly characterized by short attention spans and snapshot-based viewing, often employing line charts to convey trends and patte…
How Does Title Framing Influence Pattern Identification in Line Charts?
Jasmine Lim, Tapendra Pandey, Arran Zeyu Wang +2
Visual data communication in digital media is increasingly characterized by short attention spans and snapshot-based viewing, often employing line charts to convey trends and patte…
CatPAL: Task-Aware Learning for Categorical Palette Recommendation
Chin Tseng, Arran Zeyu Wang, Yunqi Li +1
Designing effective categorical palettes requires balancing a range of factors, including perceptual distinctiveness, category count, and task effectiveness. The effectiveness of c…
Multimodal Data Comprehension: Understanding How Visual-Textual Chains of Information Influence Data Interpretation
Arran Zeyu Wang, Fuling Sun, Danielle Albers Szafir
Visualizations and text often work together to support effective data communication. Despite this common paradigm, we know little about how the interplay of these modalities affect…
Contextualization or Rationalization? The Effect of Causal Priors on Data Visualization Interpretation
Arran Zeyu Wang, David Borland, Estella Calcaterra +1
Understanding how individuals interpret charts is a crucial concern for visual data communication. This imperative has motivated a number of studies, including past work demonstrat…
Redundant is Not Redundant: Automating Efficient Categorical Palette Design Unifying Color & Shape Encodings with CatPAW
Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri +1
Colors and shapes are commonly used to encode categories in multi-class scatterplots. Designers often combine the two channels to create redundant encodings, aiming to enhance clas…
Graphical Perception of Icon Arrays versus Bar Charts for Value Comparisons in Health Risk Communication
Jade Kandel, Jiayi Liu, Arran Zeyu Wang +2
Visualizations support critical decision making in domains like health risk communication. This is particularly important for those at higher health risks and their care providers,…
Visual Analytics for Causal Reasoning from Real-World Health Data
Arran Zeyu Wang, David Borland, David Gotz
The increasing capture and analysis of large-scale longitudinal health data offer opportunities to improve healthcare and advance medical understanding. However, a critical gap exi…
Characterizing Visualization Perception with Psychological Phenomena: Uncovering the Role of Subitizing in Data Visualization
Arran Zeyu Wang, Ghulam Jilani Quadri, Mengyuan Zhu +2
Understanding how people perceive visualizations is crucial for designing effective visual data representations; however, many heuristic design guidelines are derived from specific…
Screen Reader Programmers in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape
Nan Chen, Luna K. Qiu, Arran Zeyu Wang +2
Generative AI agents are reshaping human-computer interaction, shifting users from direct task execution to supervising machine-driven actions, especially the rise of "vibe coding"…
Striking the Right Balance: Systematic Assessment of Evaluation Method Distribution Across Contribution Types
Feng Lin, Arran Zeyu Wang, Md Dilshadur Rahman +2
In the rapidly evolving field of information visualization, rigorous evaluation is essential for validating new techniques, understanding user interactions, and demonstrating the e…
Shape It Up: An Empirically Grounded Approach for Designing Shape Palettes
Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri +1
Shape is commonly used to distinguish between categories in multi-class scatterplots. However, existing guidelines for choosing effective shape palettes rely largely on intuition a…
Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis
Arran Zeyu Wang, David Borland, David Gotz
Providing effective guidance for users has long been an important and challenging task for efficient exploratory visual analytics, especially when selecting variables for visualiza…
Causal Priors and Their Influence on Judgements of Causality in Visualized Data
Arran Zeyu Wang, David Borland, Tabitha C. Peck +2
"Correlation does not imply causation" is a famous mantra in statistical and visual analysis. However, consumers of visualizations often draw causal conclusions when only correlati…
Our Stories, Our Data: Co-designing Visualizations with People with Intellectual and Developmental Disabilities
Keke Wu, Ghulam Jilani Quadri, Arran Zeyu Wang +4
Individuals with Intellectual and Developmental Disabilities (IDD) have unique needs and challenges when working with data. While visualization aims to make data more accessible to…
Revisiting Categorical Color Perception in Scatterplots: Sequential, Diverging, and Categorical Palettes
Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri +1
Existing guidelines for categorical color selection are heuristic, often grounded in intuition rather than empirical studies of readers' abilities. While design conventions recomme…
Do You See What I See? A Qualitative Study Eliciting High-Level Visualization Comprehension
Ghulam Jilani Quadri, Arran Zeyu Wang, Zhehao Wang +3
Designers often create visualizations to achieve specific high-level analytical or communication goals. These goals require people to naturally extract complex, contextualized, and…
An Empirical Study of Counterfactual Visualization to Support Visual Causal Inference
Arran Zeyu Wang, David Borland, David Gotz
Counterfactuals -- expressing what might have been true under different circumstances -- have been widely applied in statistics and machine learning to help understand causal relat…
Using Counterfactuals to Improve Causal Inferences from Visualizations
David Borland, Arran Zeyu Wang, David Gotz
Traditional approaches to data visualization have often focused on comparing different subsets of data, and this is reflected in the many techniques developed and evaluated over th…