StreetArt4Sustainability dataset: Mapping aesthetic emotions to street art

A novel dataset of 556 street art images is presented, accompanied by affective evaluations from 1,239 Portuguese and Brazilian participants. Artworks were selected to reflect themes associated with the United Nations Sustainable Development Goals. Using a stimulus-sampling design, each participant completed an online survey in which 10 randomly selected artworks were presented and reported their responses in terms of valence, arousal, and specific emotion labels (being moved, awe, inspiration, hope, sadness, fear, anger, emotional connection, reflection, awareness, and interest), as well as their interest in street art and sustainability consciousness. Multilevel analyses showed that higher interest in street art and greater sustainability consciousness were consistent predictors of more positive emotional responses to the artworks. In contrast, the effects of gender and age were negligible, and national differences emerged only for feeling moved and awe. Network analyses revealed a highly interconnected emotional structure, with three clusters: self-transcendent, epistemic, and negative emotions. Feeling moved and emotional connection occupied central bridging positions, showing both direct and indirect links across positive and negative emotion clusters. Overall, these findings indicate that street art evokes a broad range of interconnected self-transcendent, cognitive-epistemic, and negative emotions, highlighting the complexity of viewers' responses to the artworks. The dataset provides a valuable resource for research on emotional responses to street art and can support broader investigations into visual perception, aesthetic processing, and the communication of sustainability-related themes.

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Publication Details

Journal
Behavior Research Methods
Published
2026-07-24
DOI
https://doi.org/10.3758/s13428-026-03119-5
Primary Topic
Aesthetic Perception and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

StreetArt4Sustainability dataset: Mapping aesthetic emotions to street art

Erin Michelle Buchanan, Patrí­cia Arriaga
Behavior Research Methods
Aesthetic Perception and Analysis
article

StreetArt4Sustainability dataset: Mapping aesthetic emotions to street art

Erin Michelle Buchanan, Patrí­cia Arriaga
article en

Abstract

A novel dataset of 556 street art images is presented, accompanied by affective evaluations from 1,239 Portuguese and Brazilian participants. Artworks were selected to reflect themes associated with the United Nations Sustainable Development Goals. Using a stimulus-sampling design, each participant completed an online survey in which 10 randomly selected artworks were presented and reported their responses in terms of valence, arousal, and specific emotion labels (being moved, awe, inspiration, hope, sadness, fear, anger, emotional connection, reflection, awareness, and interest), as well as their interest in street art and sustainability consciousness. Multilevel analyses showed that higher interest in street art and greater sustainability consciousness were consistent predictors of more positive emotional responses to the artworks. In contrast, the effects of gender and age were negligible, and national differences emerged only for feeling moved and awe. Network analyses revealed a highly interconnected emotional structure, with three clusters: self-transcendent, epistemic, and negative emotions. Feeling moved and emotional connection occupied central bridging positions, showing both direct and indirect links across positive and negative emotion clusters. Overall, these findings indicate that street art evokes a broad range of interconnected self-transcendent, cognitive-epistemic, and negative emotions, highlighting the complexity of viewers' responses to the artworks. The dataset provides a valuable resource for research on emotional responses to street art and can support broader investigations into visual perception, aesthetic processing, and the communication of sustainability-related themes.

Behavior Research MethodsVol. 58(9)
Harrisburg University of Science and Technology (US), Iscte – Instituto Universitário de Lisboa (PT)
ISCTE – Instituto Universitário de Lisboa
Openalex Percentile: Top 7%
Aesthetic Perception and Analysis
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StreetArt4Sustainability dataset: Mapping aesthetic emotions to street art — Erin Michelle Buchanan, Patrí­cia Arriaga · Behavior Research Methods (2026) | TGRS Research Map | TGRS