Detecting and defending against seizure-inducing GIFs in social media

  author    = {South, Laura and Saffo, David, and Borkin, Michelle A.},
  booktitle = {Proc. {CHI} Conference on Human Factors in Computing Systems},
  title     = {Detecting and defending against seizure-inducing {GIF}s in social media},
  year      = {2021},
  note      = {Preprint \& supplemental material:},
  series    = {CHI},
  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},
  doi       = {10.1145/3411764.3445510},

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