The Co-Evolution of Language, Technology, and Culture in Autism Computing Research: Lessons Learned From ACM Digital Library

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Koronthály, D., Heffelman, A., Magsi, H., Zuber, W., Sharmin, M., & Ahmed, S. (2025). The Co-Evolution of Language, Technology, and Culture in Autism Computing Research: Lessons Learned From ACM Digital Library. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9(4), 1-31. https://doi.org/10.1145/3770638

Publication date: 2 Dec 2025 Added to AutiHub: 20 Oct 2026 Type: Article Article language: English
Publisher source (DOI) Full text OpenAlex source

This publication is integrated into AutiHub through:

Authors

Publication authors
6
Publication authors identified as autistic
0 / 6 (0.0%)
  1. Daniel Koronthály
  2. Adrian Heffelman
  3. Hamza Magsi
  1. Wil Zuber
  2. Moushumi Sharmin
  3. Shameem Ahmed

Abstract

In the last two decades, autism research in computing has experienced tremendous growth, highlighting the potential to improve the experience of autistic individuals. Our research offers a detailed understanding of the landscape of autism computing research in the ACM Digital Library by conducting a literature review (N=533). Our analysis reveals that autism computing research lacks inclusiveness in several important demographic dimensions, including gender identity, age, and culture. The developed technology is largely focused on diagnosis (e.g., autism detection) and addressing the needs of autistic children (e.g., improving social communication) while ignoring the challenges of autistic elderly and adults (e.g., independent living and employment). Also, autism computing research in the ACM Digital Library is concentrated in North America and Europe, with no or little representation from Africa, South America, and Oceania. We identify areas that deserve attention and provide actionable guidelines to enhance the inclusiveness and generalizability of autism research in computing.

Bibliography cited by this reference

Cited references are imported from external metadata sources when they are available. The list may be partial.

Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 28 Oct 2026 01:01.

Cited references
65
With a DOI
40
Without a DOI, from raw bibliography text
25
10 / 65 (15.4%) cited references include at least one author identified as autistic.
References with data to complete
3 / 65 (4.6%)
References with detected author names
62 / 65 (95.4%)
Without detected author names
3
Without a structured title
3
Without a stable identifier
25
References with raw author names still to review
3
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
186
From DOI or external metadata
186
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
3
60 / 186 (32.3%) names are linked to an author already present in AutiHub. 126 / 186 (67.7%) names are not yet linked.
Names linked to a person identified as autistic
15 / 186 (8.1%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 15 / 60 (25.0%). Distinct people identified as autistic: 15 / 179 (8.4%).
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