SAID: A Social Media AI-generated Interface Dataset Using Prompt Engineering Methods Focused On Accessibility

We present SAID (Social Media AI-generated Interface Dataset), a systematically curated collection of 240 social media profile interfaces generated through controlled prompt engineering focused on accessibility. As AI tools reshape interface design practices, understanding how these systems interpret and implement accessibility requirements in social media interfaces becomes more and more important. Through six distinct prompt categories examining both generic and specific accessibility requirements, our dataset captures how AI systems interpret and implement accessibility features across visual and motor impairment dimensions. The dataset combines complete interface designs in multiple formats (PNG and SVG), detailed prompt engineering methodology, and comprehensive documentation of interface components such as social identity presentation, content engagement, navigation, and interactive elements. SAID enables novel research directions from understanding AI's role in shaping accessible social media experiences to examining how automated design tools can support more inclusive social interactions.

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Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35947
Primary Topic
Digital Accessibility for Disabilities
Type
article
Field-Weighted Citation Impact
0.00
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article

SAID: A Social Media AI-generated Interface Dataset Using Prompt Engineering Methods Focused On Accessibility

Alexandra-Elena Guriță
Proceedings of the International AAAI Conference on Web and Social Media
Digital Accessibility for Disabilities
article

SAID: A Social Media AI-generated Interface Dataset Using Prompt Engineering Methods Focused On Accessibility

Alexandra-Elena Guriță
article en

Abstract

We present SAID (Social Media AI-generated Interface Dataset), a systematically curated collection of 240 social media profile interfaces generated through controlled prompt engineering focused on accessibility. As AI tools reshape interface design practices, understanding how these systems interpret and implement accessibility requirements in social media interfaces becomes more and more important. Through six distinct prompt categories examining both generic and specific accessibility requirements, our dataset captures how AI systems interpret and implement accessibility features across visual and motor impairment dimensions. The dataset combines complete interface designs in multiple formats (PNG and SVG), detailed prompt engineering methodology, and comprehensive documentation of interface components such as social identity presentation, content engagement, navigation, and interactive elements. SAID enables novel research directions from understanding AI's role in shaping accessible social media experiences to examining how automated design tools can support more inclusive social interactions.

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
Ştefan cel Mare University of Suceava (RO)
Openalex Percentile: Top 79%
Digital Accessibility for Disabilities
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