Understanding and Classifying Online Amputee Users on Reddit

ABSTRACT

Accessibility researchers have difficulty recruiting representative participants with disabilities given their scarcity. The rich information on social media provides accessibility researchers with a new approach to collecting data about these populations. Because social media is used by multiple stakeholders, a major barrier to this approach is differentiating representative users who have disabilities from unrepresentative users who do not. We (1) introduce an empirical study that compares representative users who are amputees with unrepresentative users in terms of linguistic behavior, online interaction, and community characteristics on Reddit and (2) develop a feature extraction method based on statistical analyses and graph mining to classify representative users. Those features allow us to detect amputees using a supervised learning method with an overall accuracy of 88% in amputee-related subreddits. Our findings improve our understanding of anonymous online users with physical disabilities, and can inform better tools for online data collection for accessibility researchers.

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• Human-centered computing

  • Human computer interaction (HCI)

    • Interaction paradigms

• Information systems

  • Information retrieval