Mirroring Minds: Asymmetric Linguistic Accommodation and Diagnostic Identity in ADHD and Autism Reddit Communities
Year: 2026
Type: conference-paper
Abstract: Social media research on mental health has focused predominantly on detecting and diagnosing conditions at the individual level.In this work, we shift attention to intergroup behavior, examining how two prominent neurodivergent communities, ADHD and autism, adjust their language when engaging with each other on Reddit.Grounded in Communication Accommodation Theory (CAT), we first establish that each community maintains a distinct linguistic profile as measured by the Linguistic Inquiry and Word Count (LIWC) dictionary.We then show that these profiles shift in opposite directions when users cross community boundaries: features that are elevated in one group's home community decrease when its members post in the other group's space, and vice versa, consistent with convergent accommodation.We further demonstrate the practical stakes of this accommodation: classifiers trained to distinguish the two communities from their in-group language lose roughly 30 percentage points of accuracy, falling below chance, when applied to the same users' cross-community posts, confirming that accommodation, not just diagnosis, drives their predictions.Finally, in an exploratory longitudinal analysis around the moment of public diagnosis disclosure, we find that its effects on linguistic style are small and, in some cases, directionally opposite to crosscommunity accommodation, providing initial evidence that situational audience adaptation and longer-term identity processes may involve different mechanisms.Our findings contribute to understanding intergroup communication dynamics among neurodivergent populations online and carry implications for community moderation and clinical perspectives on these conditions.
Institutions: George Washington University, Texas A&M University
Language: English
Topic: Mental Health via Writing
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7166802709
