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. We summarize recommendations from other fields for best practices with Likert data in visualization evaluations, based on the results of our survey. A full copy of this paper and all supplementary material are available at https://osf.io/exbz8/.

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 ex-tension 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 mediaplatforms and contribute recommendations for improving online accessibility for individuals with photosensitivity. All study materialsare available at https://osf.io/5a3dy/.

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.

The creator uses a risk detection system and removes the harmful sequences before releasing the animation. The user is safe.The attacker intentionally sidesteps creator-driven protections.The user is at risk! Creator-driven protection ACCIDENTAL ATTACK Consumer-driven protectionThe dangerous content is flagged and removed before it is seen by the user. The user is safe. Consumer-driven protectionThe dangerous content is flagged and removed before it is seen by the user. The user is safe.A content creator accidentally makes an animation with seizure-inducing content.A dangerous animation is created with the explicit goal of causing a seizure. Figure 1: Flashing and strobing GIFs can cause seizures and even death when viewed by people with photosensitive epilepsy (PSE).Creator-driven systems rely on content creators to actively check their work for seizure-inducing content before releasing it online, leaving photosensitive individuals vulnerable when creators avoid such protections out of ignorance or malice. Consumer-driven systems protect users in both accidental and malicious attack scenarios.

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.