The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness
Open accessAbstract
Users make lasting judgments about a website's appeal within a split second of seeing it for the first time. This first impression is influential enough to later affect their opinions of a site's usability and trustworthiness. In this paper, we demonstrate a means to predict the initial impression of aesthetics based on perceptual models of a website's colorfulness and visual complexity. In an online study, we collected ratings of colorfulness, visual complexity, and visual appeal of a set of 450 websites from 548 volunteers. Based on these data, we developed computational models that accurately measure the perceived visual complexity and colorfulness of website screenshots. In combination with demographic variables such as a user's education level and age, these models explain approximately half of the variance in the ratings of aesthetic appeal given after viewing a website for 500ms only.
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Cites
Assessing dimensions of perceived visual aesthetics of web sites
Lavie, T., & Tractinsky, N. (2004) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2003.09.002 · Cited by 1,335
Studying Aesthetics in Photographic Images Using a Computational Approach
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744078_23 · Cited by 1,107
Attention web designers: You have 50 milliseconds to make a good first impression!
Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006) · Behaviour & Information Technology · doi:10.1080/01449290500330448 · Cited by 1,025
Rosenholtz, R., Li, Y., & Nakano, L. (2007) · Journal of Vision · doi:10.1167/7.2.17 · Cited by 796
Modeling Web Site Design Across Cultures: Relationships to Trust, Satisfaction, and E-Loyalty
Cyr, D. (2008) · Journal of Management Information Systems · doi:10.2753/mis0742-1222240402 · Cited by 766
Measuring colorfulness in natural images
Hasler, D., & Suesstrunk, S. E. (2003) · SPIE Proceedings · doi:10.1117/12.477378 · Cited by 729
Studies in the New Experimental Aesthetics
Alluisi, E. A., & Berlyne, D. E. (1975) · The American Journal of Psychology · doi:10.2307/1421783 · Cited by 558
Colour appeal in website design within and across cultures: A multi-method evaluation
Cyr, D., Head, M., & Larios, H. (2010) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2009.08.005 · Cited by 511
Sonderegger, A., & Sauer, J. (2010) · Applied Ergonomics · doi:10.1016/j.apergo.2009.09.002 · Cited by 455
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Cited by
Rico: A Mobile App Dataset for Building Data-Driven Design Applications
Deka, B., Huang, Z., Franzen, C., Hibschman, J., Afergan, D., Li, Y., Nichols, J., & Kumar, R. (2017) · Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3126594.3126651 · Cited by 482
Aalto Interface Metrics (AIM): A Service and Codebase for Computational GUI Evaluation
Oulasvirta, A., De Pascale, S., Koch, J., Langerak, T., Jokinen, J., Todi, K., Laine, M., Kristhombuge, M., Zhu, Y., Miniukovich, A., et al. (2018) · Adjunct Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3266037.3266087 · Cited by 94
The Influence of User Culture on Website Usability
Alexander, R., Thompson, N., McGill, T., & Murray, D. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102688 · Cited by 51
Ma, S., Wei, Z., Tian, F., Fan, X., Zhang, J., Shen, X., Lin, Z., Huang, J., Měch, R., Samaras, D., et al. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300701 · Cited by 24
Fu, Y., Zhou, T., Han, B., Wang, M., Chen, Y., Gomes Da Costa Lai, Z., Pang, R. Y., Reinecke, K., Wobbrock, J. O., & Hiniker, A. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791329 · Cited by 2
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Metadata
- Authors
- Reinecke, K., Yeh, T., Miratrix, L., Mardiko, R., Zhao, Y., Liu, J., & Gajos, K. Z.
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2013-04-27
- Pages
- 2049-2058
- OpenAlex
- W2166261011
- Cited by
- 305
- References
- 35
- FWCI
- 17.13
- Type
- conference paper
- Language
- en
- Open access
- green
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- Reinecke, K., Yeh, T., Miratrix, L., Mardiko, R., Zhao, Y., Liu, J., & Gajos, K. Z. (2013). Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/2470654.2481281
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