{"title":"通过大规模分析检查基于图像的按钮标签在Android应用程序中的可访问性","authors":"A. S. Ross, Xiaoyi Zhang, J. Fogarty, J. Wobbrock","doi":"10.1145/3234695.3236364","DOIUrl":null,"url":null,"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.","PeriodicalId":110197,"journal":{"name":"Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility","volume":"29 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"Examining Image-Based Button Labeling for Accessibility in Android Apps through Large-Scale Analysis\",\"authors\":\"A. S. Ross, Xiaoyi Zhang, J. Fogarty, J. Wobbrock\",\"doi\":\"10.1145/3234695.3236364\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":110197,\"journal\":{\"name\":\"Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility\",\"volume\":\"29 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3234695.3236364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3234695.3236364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Examining Image-Based Button Labeling for Accessibility in Android Apps through Large-Scale Analysis
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.