Photosensitive Accessibility for Interactive Data Visualizations

Published in IEEE VIS Conference Proceedings, 2022

Accessibility guidelines place restrictions on the use of animations and interactivity on webpages to lessen the likelihood of webpages inadvertently producing sequences with flashes, patterns, or color changes that may trigger seizures for individuals with photosensitive epilepsy. Online data visualizations often incorporate elements of animation and interactivity to create a narrative, engage users, or encourage exploration. These design guidelines have been empirically validated by perceptual studies in visualization literature, but the impact of animation and interaction in visualizations on users with photosensitivity, who may experience seizures in response to certain visual stimuli, has not been considered. We systematically gathered and tested 1,132 interactive and animated visualizations for seizure-inducing risk using established methods and found that currently available methods for determining photosensitive risk are not reliable when evaluating interactive visualizations, as risk scores varied significantly based on the individual interacting with the visualization. To address this issue, we introduce a theoretical model defining the degree of control visualization designers have over three determinants of photosensitive risk in potentially seizure-inducing sequences: the size, frequency, and color of flashing content. Using an analysis of 375 visualizations hosted on, we created a theoretical model of photosensitive risk in visualizations by arranging the photosensitive risk determinants according to the degree of control visualization authors have over whether content exceeds photosensitive accessibility thresholds. We then use this model to propose a new method of testing for photosensitive risk that focuses on elements of visualizations that are subject to greater authorial control — and are therefore more robust to variations in the individual user — producing more reliable risk assessments than existing methods when applied to interactive visualizations.

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Effective Use of Likert Scales in Visualization Evaluations: A Systematic Review

Published in Eurovis/Computer Graphics Forum, 2022

Likert scales are often used in visualization evaluations to produce quantitative estimates of subjective attributes, such as ease of use or aesthetic appeal. However, the methods used to collect, analyze, and visualize data collected with Likert scales are inconsistent among evaluations in visualization papers. In this paper, we examine the use of Likert scales as a tool for measuring subjective response in a systematic review of 134 visualization evaluations published between 2009 and 2019. We find that papers with both objective and subjective measures do not hold the same reporting and analysis standards for both aspects of their evaluation, producing less rigorous work for the subjective qualities measured by Likert scales. Additionally, we demonstrate that many papers are inconsistent in their interpretations of Likert data as discrete or continuous and may even sacrifice statistical power by applying nonparametric tests unnecessarily. Finally, we identify instances where key details about Likert item construction with the potential to bias participant responses are omitted from evaluation methodology reporting, inhibiting the feasibility and reliability of future replication studies.

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Detecting and Defending Against Seizure-Inducing GIFs in Social Media

Published in ACM CHI Conference Proceedings, 2021

Despite recent improvements in online accessibility, the Internet remains an inhospitable place for users with photosensitive epilepsy, a chronic condition in which certain light stimuli can trigger seizures and even lead to death in extreme cases. In this paper, we explore how current risk detection systems have allowed attackers to take advantage of design oversights and target vulnerable users with photosensitivity on popular social media platforms. Through interviews with photosensitive individuals and a critical review of existing systems, we constructed design requirements for consumer-driven protective systems and developed a prototype browser extension for actively detecting and disarming potentially seizure-inducing GIFs and videos. We validate our system with a comprehensive dataset of simulated GIFs and GIFs collected from social media. Finally, we conduct a novel quantitative analysis of the prevalence of seizure-inducing GIFs across popular social media platforms and contribute recommendations for improving online accessibility for individuals with photosensitivity. All study materials are available on OSF.

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Generating Seizure-Inducing Sequences with Interactive Visualizations

Published in IEEE VIS Poster, 2020

Interactive visualizations are often built to draw the eye towards pertinent information with attention-grabbing pops of color and patterns. These techniques, though helpful in engaging the average user and nudging them towards important information, can be harmful to users with photosensitive epilepsy, who may experience seizures when exposed to content with flashes, transitions to and from saturated red, or repeated patterns. In this paper, we explore three case studies of interactive visualizations created without malicious intent yet capable of producing seizure-inducing sequences through interaction alone. Based on these case studies as well as relevant related literature, we contribute a set of simple recommendations to help visualization designers and developers avoid accidentally creating interactive visualizations with the potential to cause seizures.

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DebateVis: Visualizing Political Debates for Non-Expert Users

Published in IEEE VIS Conference Proceedings, 2020

Political debates provide an important opportunity for voters to observe candidate behavior, learn about issues, and make voting decisions. However, debates are generally broadcast late at night and last more than ninety minutes, so watching debates live can be inconvenient, if not impossible, for many potential viewers. Even voters who do watch debates may find themselves overwhelmed by a deluge of information in a substantive, issue-driven debate. Media outlets produce short summaries of debates, but these are not always effective as a method of deeply comprehending the policies candidates propose or the debate techniques they employ. In this paper we contribute reflections and results of an 18-month design study through an interdisciplinary collaboration with journalism and political science researchers. We characterize task and data abstractions for visualizing political debate transcripts for the casual user, and present a novel tool (DEBATEVIS) to help non-expert users explore and analyze debate transcripts.

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Ethical Considerations of Photosensitive Epilepsy in Mixed Reality

Published in CHI 2020 Workshop: Exploring Potentially Abusive Ethical, Social and Political Implications of Mixed Reality Research in HCI, 2020

As public interest in virtual and augmented reality increases, so do the risks faced by users with photosensitive epilepsy, a neurological condition where seizures are triggered by specific kinds of light stimuli. Most research on photosensitive epilepsy focuses on user interaction with television sets and does not necessarily transfer to other methods of interaction. Very little research has been done examining mixed reality from the perspective of photosensitive users and understanding the additional risks posed by new forms of immersive technology. Examples of hackers targeting people with photosensitive epilepsy through social media serve as a wake-up call about the possibility of similar malicious attacks in mixed reality. In this paper we draw from photosensitive epilepsy research to create recommendations for simple steps mixed reality developers can take to minimize photosensitive risk in their systems in addition to issuing a broader call for further research into understanding photosensitive epilepsy in the context of mixed reality.

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