,
Nico Van de Weghe
,
Wim Fias
,
Haosheng Huang
Creative Commons Attribution 4.0 International license
Street View Imagery (SVI) is widely used to study perceived street safety, yet most studies treat safety as a general impression of urban scenes and rely mainly on daytime imagery. It remains unclear whether safety judgments differ across evaluative framings, defined here as the safety question asked of participants, and whether this difference varies between daytime and nighttime scenes. We analyzed 7,320 safety ratings from 61 participants for 120 SVIs, including 60 daytime and 60 nighttime images. Participants judged scenes under two evaluative framings: crime-related safety and traffic-related safety. Using cumulative link mixed models with random intercepts for participants and stimuli, we found that the stimulus set received higher safety ratings in the crime-related framing than in the traffic-related framing. This evaluative-framing effect was stronger for daytime than for nighttime scenes. These findings indicate that perceived street safety in SVI is not a fixed property of image content, but also depends on the safety question asked during judgment.
@InProceedings{qin_et_al:LIPIcs.COSIT.2026.32,
author = {Qin, Tong and Van de Weghe, Nico and Fias, Wim and Huang, Haosheng},
title = {{The Same Street, Different Safety Judgments: Evaluative Framing Effects in Daytime and Nighttime Street View Imagery}},
booktitle = {17th International Conference on Spatial Information Theory (COSIT 2026)},
pages = {32:1--32:7},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-438-3},
ISSN = {1868-8969},
year = {2026},
volume = {393},
editor = {Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.32},
URN = {urn:nbn:de:0030-drops-275763},
doi = {10.4230/LIPIcs.COSIT.2026.32},
annote = {Keywords: street view imagery, spatial cognition, safety perception, evaluative framing, geographic information science}
}