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Stigma Management Strategies of Autistic Social Media Users

Koteyko, N., Van Driel, M., Billan, S. , Barros Pena, B. ORCID: 0000-0003-4035-1860 & Vines, J. (2024). Stigma Management Strategies of Autistic Social Media Users. Autism in Adulthood, doi: 10.1089/aut.2023.0095

Abstract

Background: Research on stigma management strategies in autism relies on questionnaires or experiments, leading to a gap in understanding of how to identify the strategies in naturalistic interactions. The identification of individual (adapting minority group characteristics) and collective (positively redeveloping the in-group) stigma management strategies in online communication is important for understanding how to improve the quality of social media experiences for autistic users.

Methods: Using linguistic analysis and engaging with ethnographic perspectives on relationship management, this article develops a novel approach to the identification of individual and collective stigma management strategies of autistic social media users. We combine online observation and interviews with 34 autistic social media users with a corpus-assisted analysis of their posts, divided into two groups according to regular or limited mentions of autism.

Results: We show that posts in the first group focus on information provision and exchange and include markers of shared understanding and community building as part of a collective strategy. Interviews with the authors reveal a strong sense of autistic identity and highlight the importance of staying true to one's specific communicative preferences. Posts in the second group are characterized by tentative language (e.g., “seem” and “not sure”) as a way of avoiding social threats by users who report uncertainty and anxiety about misinterpretation of their messages.

Conclusions: We show that autistic social media users have specific preferences in how they communicate and express connection online. However, due to negative experiences of social interactions some do not follow these preferences and instead select linguistic and visual resources that can reduce perceived risks of misunderstanding. We question the claims that the internet is inherently enabling for autistic users and call for further research and policy effort to ensure autistic sociality rights in all digital environments.

Community brief

Why is this an important issue?
Autistic people often change their behavior to fit in with nonautistic social environment (thereby “camouflaging” their differences), in person and online. The internet is also a place where autistic people interact with each other and build community. However, research on these online behaviors is mostly focused on conscious actions people can recall when answering survey questions.

What was the purpose of this study, and what did the researchers do?
We wanted to find out whether it is possible to identify both community building strategies and camouflaging from the language used on social media, as some behaviors may happen without people realizing it. This article uses a method called digital linguistic ethnography to study how 34 autistic adult social media users managed the way they are seen online. The method involved observing where and how participants posted messages and comparing the frequency of word use between participants who regularly mentioned autism in their posts and those who did not. We also interviewed participants about their social media experiences and motivations.

What were the results of the study?
The results show that participants who mentioned autism used language in specific ways to raise awareness and connect with others. Participants who did not mention autism used more tentative language (e.g., “might,” “seem,” and “not sure”) and worried about being misunderstood.

What do these findings add to what was already known?
The findings are important as they show that autistic people have specific preferences in how they communicate and express connection on social media. The findings also show that some autistic adults may feel unable to follow these preferences when interacting online, which contradicts previous assumptions that autistic people do not need to mask in online environments.

What are the potential weaknesses of the study?
Although our participants exhibited a range of internet skills, they may represent a subgroup that is particularly inclined toward social media usage and interaction. This means that our findings may not apply for autistic adults with learning difficulties, for example. Our sample also includes only speaking individuals without the history of intellectual disabilities, which means that that the experiences of nonspeaking autistic people are not represented.

How will these findings help autistic adults now or in the future?
The findings inform our understanding of what kinds of social media situations make autistic people feel like they fit in or feel uncomfortable. This is important for designing online environments that are inclusive of autistic communicative preferences and have the potential to improve the quality of online social experiences for autistic people.

Publication Type: Article
Additional Information: This is the accepted version of the following article: Koteyko, N., Van Driel, M., Billan, S. , Barros Pena, B. & Vines, J. (2024). Stigma Management Strategies of Autistic Social Media Users. Autism in Adulthood, which has now been formally published in final form at Autism in Adulthood at https://dx.doi.org/10.1089/aut.2023.0095. This original submission version of the article may be used for non-commercial purposes in accordance with the Mary Ann Liebert, Inc., publishers’ self-archiving terms and conditions.
Publisher Keywords: autism, digital communication and interaction, stigma, social media
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HM Sociology
H Social Sciences > HN Social history and conditions. Social problems. Social reform
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine
Departments: School of Science & Technology
School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > Human Computer Interaction Design
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