Year: 2025
Type: article
Abstract: Text-to-image generation (AI art) has become a mainstream phenomenon since the introduction of DALL-E by OpenAI in January 2021 (Nast, 2023). ). On the one hand, AI art challenges definitions of creativity that center on anthropocentric values and discredits the contributions of artists in the training of these AI models (Knibbs, 2023). On the other hand, it blurs the line between artists and non-artists by enabling new ways of creating art (e.g., prompt engineering: an iterative and experimental text-based process to interact with text-to-image generation models). Regardless of one’s ethical stance, practitioners of AI art, including artists of various skills and non-artists, form and participate in online communities to showcase their wares, share practices and resources, and learn from each other. This study uses a topic modeling approach to examine topics within three subreddit communities centered on three text-to-image generation models (r/StableDiffusion, r/midjourney, and r/weirddalle). The analysis, based on the top 500 posts from each subreddit over one month, reveals distinct community foci: r/StableDiffusion emphasizes technological innovations and technical learning, r/midjourney showcases AI art and prompt learning, while r/weirddalle is more competitive, focusing on creative or entertaining results. The study further derives topics from prompts extracted from the images, revealing preferences for popular media characters, high photorealism, and surrealist styles, with a notable emphasis on portraits of women.
Authors: Jing Han, Andrew Iliadis
Institution: Temple University
Language: English
Topic: Art, Technology, and Culture
Subfield: Visual Arts and Performing Arts
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4407195429