The Beauty Survey
Open accessAbstract
This repository contains the data collected during and the code used to analyze the Beauty Survey. A pre-print of the associated paper including our analysis and findings can be found at this link. Zip files have been uploaded to this repository to stay within the file limit enforced by Zenodo. To use our code and data simply unzip these folders while mainting the current directory structure. While the code here is complete and stands on its own, any new features added can be found in the GitHub repository associated with this project (link). AG and NO are supported by a nominal grant received at the ELLIS Unit Alicante Foundation from the Regional Government of Valencia in Spain (Convenio Singular signed with Generalitat Valenciana, Conselleria de Innovacion, Industria, Comercio y Turismo, Direccion General de Innovacion), along with grants from the European Union’s Horizon 2020 research and innovation programme - ELISE (grant agreement 951847) and ELIAS (grant agreement 101120237), and by grants from the Banc Sabadell Foundation and Intel corporation. BL is partially supported by the European Union’s Horizon Europe research and innovation program under grant agreement No. 101120237 (ELIAS) and by the PNRR project FAIR - Future AI Research (PE00000013), under the NRRP MUR program funded by the NextGenerationEU.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The data collected in the study has been deposited in a public online repository.
“The data collected in the study has been deposited in a public online repository [112].”
From What is beautiful is still good: the attractiveness halo effect in the era of beauty filters (2024) · cites this paper as [112]
Cited by
Sorted by citations
What is beautiful is still good: the attractiveness halo effect in the era of beauty filters
Gulati, A., Martínez-Garcia, M., Fernández, D., Lozano, M. A., Lepri, B., & Oliver, N. (2024) · Royal Society Open Science · doi:10.1098/rsos.240882 · Cited by 21 · see citing works
Self-citation
- Authors
- Gulati, A., Oliver, N., Lepri, B., & Alicante, E.
- Affiliations
- ELLIS Alicante (ES)
- Fondazione Bruno Kessler (IT)
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2024-09-25
- OpenAlex
- W7223735378
- Cited by
- 0
- References
- 0
- Type
- dataset
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Aesthetics, and Perception
- Keywords
- beauty, perception of beauty, aesthetic preference
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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