Contemporary architectural aesthetic preferences based on popular AI images and models of the Civitai architect community

Architects often struggle to understand the architectural aesthetic preferences of their clients. At the same time, attention has been given to how individuals in artificial intelligence (AI) architect communities express these preferences. This study explores contemporary architectural aesthetic trends by analyzing content from the AI drawing platform Civitai. A multiphase research approach analyzed a dataset of 2,000 popular architectural images and 10 architectural models. In the literature review phase, 13 high-quality studies were selected to identify key indicators for evaluating architectural aesthetics. The study phase involved rigorous reviews of data characteristics, resulting in two sets of statistical results. The drawing verification phase utilized three of the most popular architectural renderings and models to validate the findings. The study reveals that ultra-modern and futuristic architecture is emerging as a new style, accounting for 69.9% of the total usage of architectural preferences. AI community users articulate their architectural aesthetic preferences, prioritizing a building's structure and external environment. Specifically, the "structure prompt" comprises 31.11%, the "structure tag" 23.37%, the "environment prompt" 20.83%, and the "environment tag" 24.5%. These results confirm that the surrounding environment plays a significant role in shaping architectural aesthetics. This study reveals emerging characteristics in contemporary architectural aesthetic preferences by AI-generated architect communities, providing valuable insights for architectural design and urban planning.

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Publication Details

Journal
Scientific Reports
Published
2025-11-26
DOI
https://doi.org/10.1038/s41598-025-25251-6
Primary Topic
Architecture and Computational Design
Type
article
Field-Weighted Citation Impact
0.00

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article

Contemporary architectural aesthetic preferences based on popular AI images and models of the Civitai architect community

Zonghui Wang, Tao Wan, Jueru Huang, Kalugina Olga Veniaminovna
Scientific Reports
Architecture and Computational Design
article

Contemporary architectural aesthetic preferences based on popular AI images and models of the Civitai architect community

Zonghui Wang, Tao Wan, Jueru Huang, Kalugina Olga Veniaminovna
article en

Abstract

Architects often struggle to understand the architectural aesthetic preferences of their clients. At the same time, attention has been given to how individuals in artificial intelligence (AI) architect communities express these preferences. This study explores contemporary architectural aesthetic trends by analyzing content from the AI drawing platform Civitai. A multiphase research approach analyzed a dataset of 2,000 popular architectural images and 10 architectural models. In the literature review phase, 13 high-quality studies were selected to identify key indicators for evaluating architectural aesthetics. The study phase involved rigorous reviews of data characteristics, resulting in two sets of statistical results. The drawing verification phase utilized three of the most popular architectural renderings and models to validate the findings. The study reveals that ultra-modern and futuristic architecture is emerging as a new style, accounting for 69.9% of the total usage of architectural preferences. AI community users articulate their architectural aesthetic preferences, prioritizing a building's structure and external environment. Specifically, the "structure prompt" comprises 31.11%, the "structure tag" 23.37%, the "environment prompt" 20.83%, and the "environment tag" 24.5%. These results confirm that the surrounding environment plays a significant role in shaping architectural aesthetics. This study reveals emerging characteristics in contemporary architectural aesthetic preferences by AI-generated architect communities, providing valuable insights for architectural design and urban planning.

Scientific ReportsVol. 15(1)
Peoples' Friendship University of Russia (RU), Jiangxi University of Water Resources and Electric Power (CN), Nanchang Institute of Science & Technology (CN)
RUDN University
Openalex Percentile: Top 64%
Architecture and Computational Design
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