Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness
Author
Yeh, Tom
Mardiko, Rahmatri
Published Version
https://doi.org/10.1145/2470654.2481281Metadata
Show full item recordCitation
Reinecke, Katharina, Tom Yeh, Luke Miratrix, Rahmatri Mardiko, Yuechen Zhao, Jenny Liu, and Krzysztof Z. Gajos. 2013. “Predicting Users’ First Impressions of Website Aesthetics with a Quantification of Perceived Visual Complexity and Colorfulness.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, April 27 - May 2, 2013, 2049-2058. New York, NY: ACM Press.Abstract
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.Terms of Use
This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAPCitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:12561368
Collections
- FAS Scholarly Articles [18256]
Contact administrator regarding this item (to report mistakes or request changes)