Toward supporting quality alt text in computing publications
Candace L. Williams, Lilian de Greef, Harris Ed, Leah Findlater, Amy Pavel, Cynthia L. Bennett
Abstract
While researchers have examined alternative (alt) text for social media and news contexts, few have studied the status and challenges for authoring alt text of figures in computing-related publications. These figures are distinct, often conveying dense visual information, and may necessitate unique accessibility solutions. Accordingly, we explored how to support authors in creating alt text in computing publications---specifically in the field of human-computer interaction (HCI). We conducted two studies: (1) an analysis of 300 recently published figures at a general HCI conference (ACM CHI), and (2) interviews with 10 researchers in HCI and related fields who have varying levels of experience writing alt text. Our findings characterize the prevalence, quality, and patterns of recent figure alt text and captions. We further identify challenges authors encounter, describing their workflow barriers and confusions around how to compose alt text for complex figures. We conclude by outlining a research agenda on process, education, and tooling opportunities to improve alt text in computing-related publications.