Work

Examining Image-Based Button Labeling for Accessibility in Android Apps through Large-Scale Analysis

Year: 2018

Type: conference-paper

Abstract: We conduct the first large-scale analysis of the accessibility of mobile apps, examining what unique insights this can provide into the state of mobile app accessibility. We analyzed 5,753 free Android apps for label-based accessibility barriers in three classes of image-based buttons: Clickable Images, Image Buttons, and Floating Action Buttons. An epidemiology-inspired framework was used to structure the investigation. The population of free Android apps was assessed for label-based inaccessible button diseases. Three determinants of the disease were considered: missing labels, duplicate labels, and uninformative labels. The prevalence, or frequency of occurrences of barriers, was examined in apps and in classes of image-based buttons. In the app analysis, 35.9% of analyzed apps had 90% or more of their assessed image-based buttons labeled, 45.9% had less than 10% of assessed image-based buttons labeled, and the remaining apps were relatively uniformly distributed along the proportion of elements that were labeled. In the class analysis, 92.0% of Floating Action Buttons were found to have missing labels, compared to 54.7% of Image Buttons and 86.3% of Clickable Images. We discuss how these accessibility barriers are addressed in existing treatments, including accessibility development guidelines.

Source: International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

DOI: 10.1145/3234695.3236364

Authors: Anne Spencer Ross, Xiaoyi Zhang, James Fogarty, Jacob O. Wobbrock

Institution: University of Washington

Language: English

Topic: Digital Accessibility for Disabilities

Subfield: Human Factors and Ergonomics

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Good health and well-being

Open Access status: bronze

Funder: National Science Foundation