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Visualization Rhetoric: Framing Effects in Narrative Visualization
It is described how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how the framework can shed light on how a visualization design prioritizes specific interpretations.
When (ish) is My Bus?: User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems
A novel discrete representation of continuous outcomes designed for small screens, quantile dotplots is proposed that reduces the variance of probabilistic estimates by ~1.15 times compared to density plots and facilitates more confident estimation by end-users in the context of realtime transit prediction scenarios.
A Deeper Understanding of Sequence in Narrative Visualization
A graph-driven approach for automatically identifying effective sequences in a set of visualizations to be presented linearly and prioritizes local (visualization-to-visualization) transitions based on an objective function that minimizes the cost of transitions from the audience perspective is proposed.
GraphScape: A Model for Automated Reasoning about Visualization Similarity and Sequencing
GraphScape is presented, a directed graph model of the vi- sualization design space that supports automated reasoning about visualization similarity and sequencing and applications are demonstrated to automatically sequence visualization presen- tations, elaborate transition paths between visualizations, and recommend design alternatives.
Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering
An alternative representation, Hypothetical Outcome Plots (HOPs), that animates a finite set of individual draws that enables viewers to infer properties of the distribution using mental processes like counting and integration.
Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making
Frequency-based visualizations previously shown to allow people to better extract probabilities (quantile dotplots) yielded better decisions, and cumulative distribution function plots performed nearly as well, and both outperformed textual uncertainty, which was sensitive to the probability interval communicated.
Mechanical Turk is Not Anonymous
While Amazon’s Mechanical Turk (AMT) online workforce has been characterized by many people as being anonymous, we expose an aspect of AMT’s system design that can be exploited to reveal a surprising
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
The characterization of interpretability work that emerges from the analysis suggests that model interpretability frequently involves cooperation and mental model comparison between people in different roles, often aimed at building trust not only between people and models but also between people within the organization.
Contextifier: automatic generation of annotated stock visualizations
The design of Contextifier is described, a novel system that automatically produces custom, annotated visualizations of stock behavior given a news article about a company.
The impact of social information on visual judgments
This work addresses how social information signals (social proof) affect quantitative judgments in the context of graphical perception, and describes how these findings can be applied to collaborative visualization systems to produce more accurate individual interpretations in social contexts.