An Analysis of Twitter Discourse Regarding Identifying Language for People on the Autism Spectrum

Abstract

Person-first language, to refer to a person with autism, has been dominant within peer-reviewed literature; however, there are autistic people who prefer identity-first language. This is a shift from the language championed within mental health nursing; therefore it is important to understand the meaning and actions within identifying language. This analysis of 29,606 words of Twitter discourse explored the political struggle between the modes of language. Differences within the conceptualisation of autism and disability underpinned varied subject positions and the rearticulation of autism and expertise was identified. Contextually driven adoption of identifying language requires awareness of the potential benefits and consequences.

Disclosure statement

The authors report no conflict of interest.

Ethical statements

This review was approved by the Southern Cross University Human Research Ethics Committee, approval ECN-18-037.

Additional information

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.