Who Tweets for the autistic community? A natural language processing-driven investigation.

Abstract

The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic community. In response to what was perceived as a misrepresentation of their interests, autistic individuals formed autistic self-advocacy groups, adopting the philosophy that autism advocacy should be led 'by' autistic people 'for' autistic people. However, recent claims that self-advocacy organisations represent only a narrow subset of the autistic community have prompted renewed debate surrounding the role of organisations in autism advocacy. While many individuals and groups have outlined their views, the debate has yet to be studied through computational means. In this study, we apply machine learning and natural language processing techniques to a large-scale collection of Tweets from organisations and individuals in autism advocacy. We conduct a specification curve analysis on the similarity of language across organisations and individuals, and find evidence to support claims of partial representation relevant to both self-advocacy groups and organisations led by non-autistic people. In introducing a novel approach to studying the long-standing conflict between different groups in the autism advocacy community, we hope to provide both organisations and individuals with new tools to help ground discussions of representation in empirical insight.Lay AbstractSome autism advocacy organisations are run by family members of autistic people, and claim to speak on behalf of autistic people. These organisations have been criticised by autistic people, who feel like autism charities do not adequately represent their true interests. In response to these organisations, autistic people have come together to form autistic self-advocacy organisations, or groups in which activists can spread awareness of autism from an autistic point-of-view. However, some people say that autistic self-advocacy organisations do not sufficiently represent the needs of all autistic people. These tensions between organisations and individuals have made it difficult to determine which organisations can make the claim that they represent all autism advocates individuals equally, instead of showing preference to a sub-group within the autism community. In this study, we try to approach this issue using computational tools to see if, in their Twitter posts, both kinds of organisations show a preference for the interests of autistic people or parents of autistic children. We do so by comparing a large body of Tweets by organisations to Tweets by autistic people and parents of autistic children. We find that both kinds of organisations match the interests of one group of autism advocates better than the other. The insight we provide has the potential to inspire new conversations and solutions to a long-standing conflict in autism advocacy.