Detecting and defending against seizure-inducing GIFs in social media

Two frames each are shown from three different GIFs. The first GIF has the message 'You deserve a seizure for your posts' shown in both frames, but the top frame is bright red and yellow while the second frame has two shades of dark blue. The second GIF is a triangular sign that says 'Alert!' and alternates between a blue-green frame and a red-yellow frame. The final GIF has the message 'epilepsy is fun!'. The color of the background behind the text is black in the first frame and white in the second.
GIFs with flashes and bright colors can cause seizures when viewed by people with photosensitive epilepsy.
Abstract
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 media platforms and contribute recommendations for improving online accessibility for individuals with photosensitivity. All study materials are available at https://osf.io/5a3dy/.
Materials
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Authors
Citation
Thumbnail image for publication titled: Detecting and defending against seizure-inducing GIFs in social media
Detecting and defending against seizure-inducing GIFs in social media

Laura South, David Saffo, and Michelle A. Borkin. In Proc. CHI Conference on Human Factors in Computing Systems—CHI. 2021. DOI: 10.1145/3411764.3445510

PDF | Preprint | DOI | Homepage | Supplement | Video Preview | Video Presentation | Preregistration | BibTeX | CHI 2022 Best Paper Honorable Mention!


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