SMU Data Science Review
Abstract
People with Autism Spectrum Disorder (ASD) have unique challenges making it difficult to interface with information on websites. In this paper, we evaluate six hundred websites for autism friendliness across four primary categories including: (Autism Focused, U.S. Federal, Google Autism Search, and Alexa Rating). Autism user requirements are linked to 29 HTML style properties and 1 image property to develop 25 novel parameterized metric components. These metric components are uniquely matched to three themes – image, animation, and font. A new Website ASD Rating score is created and applied to each website reviewed. The four website categories are comparatively evaluated based on the new Website ASD Rating score. We show that font and animation are significant features with respect to the Website ASD Rating score. The mean ASD Value score is not significant across the web site categories.
Recommended Citation
Yu, Brian; Murrietta, Michael; Horacek, Angela; and Drew, Jacob
(2018)
"A Survey of Autism Spectrum Disorder Friendly Websites,"
SMU Data Science Review: Vol. 1:
No.
2, Article 8.
Available at:
https://scholar.smu.edu/datasciencereview/vol1/iss2/8
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License