Using data from social media websites to inspire the design of assistive technology
Published in Proceedings of the 13th Web for All Conference, 2016
The rapid accumulation of user generated content on the Internet provides researchers with abundant information to extract knowledge from. It also provides HCI and accessibility practitioners with a new direction to explore and understand users requirements beyond traditional approaches. In my work, I create a tool that consists of both text-mining and machining learning methods to extract essential focuses of design out of the data collected from social networks. This tool can be used at the initial stage of a product design life-cycle by designers to collect key design aspects at a fairly low cost.