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Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature
“3,058 people like this.” In the digital age, people very commonly indicate their preferences by clicking a Like button. The data generated on the photo-sharing platform Instagram potentially represents a vast, freely accessible resource for research in the field of visual experimental aesthetics. T...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024014/ https://www.ncbi.nlm.nih.gov/pubmed/29988425 http://dx.doi.org/10.3389/fpsyg.2018.01050 |
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author | Thömmes, Katja Hübner, Ronald |
author_facet | Thömmes, Katja Hübner, Ronald |
author_sort | Thömmes, Katja |
collection | PubMed |
description | “3,058 people like this.” In the digital age, people very commonly indicate their preferences by clicking a Like button. The data generated on the photo-sharing platform Instagram potentially represents a vast, freely accessible resource for research in the field of visual experimental aesthetics. Therefore, we compiled a photo database using images of five different Instagram accounts that fullfil several criteria (e.g., large followership, consistent content). The final database consists of about 700 architectural photographs with the corresponding liking data generated by the Instagram community. First, we aimed at validating Instagram Likes as a potential measure of aesthetic appeal. Second, we checked whether previously studied low-level features of “good” image composition also account for the number of Instagram Likes that architectural photographs received. We considered two measures of visual balance and the preference for curvature over angularity. In addition, differences between images with “2D” vs. “3D” appearance became obvious. Our findings show that visual balance predicts Instagram Likes in more complex “3D” photographs, with more balance meaning more Likes. In the less complex “2D” photographs the relation is reversed, more balance led to fewer Likes. Moreover, there was a general preference for curvature in the Instagram database. Together, our study illustrates the potential of using Instagram Likes as a measure of aesthetic appeal and provides a fruitful methodological basis for future research. |
format | Online Article Text |
id | pubmed-6024014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60240142018-07-09 Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature Thömmes, Katja Hübner, Ronald Front Psychol Psychology “3,058 people like this.” In the digital age, people very commonly indicate their preferences by clicking a Like button. The data generated on the photo-sharing platform Instagram potentially represents a vast, freely accessible resource for research in the field of visual experimental aesthetics. Therefore, we compiled a photo database using images of five different Instagram accounts that fullfil several criteria (e.g., large followership, consistent content). The final database consists of about 700 architectural photographs with the corresponding liking data generated by the Instagram community. First, we aimed at validating Instagram Likes as a potential measure of aesthetic appeal. Second, we checked whether previously studied low-level features of “good” image composition also account for the number of Instagram Likes that architectural photographs received. We considered two measures of visual balance and the preference for curvature over angularity. In addition, differences between images with “2D” vs. “3D” appearance became obvious. Our findings show that visual balance predicts Instagram Likes in more complex “3D” photographs, with more balance meaning more Likes. In the less complex “2D” photographs the relation is reversed, more balance led to fewer Likes. Moreover, there was a general preference for curvature in the Instagram database. Together, our study illustrates the potential of using Instagram Likes as a measure of aesthetic appeal and provides a fruitful methodological basis for future research. Frontiers Media S.A. 2018-06-22 /pmc/articles/PMC6024014/ /pubmed/29988425 http://dx.doi.org/10.3389/fpsyg.2018.01050 Text en Copyright © 2018 Thömmes and Hübner. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Thömmes, Katja Hübner, Ronald Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title | Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title_full | Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title_fullStr | Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title_full_unstemmed | Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title_short | Instagram Likes for Architectural Photos Can Be Predicted by Quantitative Balance Measures and Curvature |
title_sort | instagram likes for architectural photos can be predicted by quantitative balance measures and curvature |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024014/ https://www.ncbi.nlm.nih.gov/pubmed/29988425 http://dx.doi.org/10.3389/fpsyg.2018.01050 |
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