Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2018
Abstract
Aesthetics plays a key role in web design. However, most websites are developed based on designers’ "inspirations" or "educated guesses" (Liu, 2003). While perceptions of aesthetics are intuitive abilities of humankind, the underlying principles for assessing aesthetics are not well understood. In this research, we propose using machine learning techniques to explore and more fully understand the patterns and underlying principles of aesthetics. We propose using machine learning techniques to develop predictive models for two aesthetic dimensions – classical aesthetics and expressive aesthetics – as well as for overall aesthetics of web pages in order to evaluate the aesthetic quality of web pages.
Keywords
Aesthetics, web aesthetics, machine learning, classical aesthetics, expressive aesthetics, overall aesthetics
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems
Research Areas
Information Systems and Management
Publication
Midwest Association for Information Systems Conference, St. Louis, Missouri, May 2018
First Page
1
Last Page
3
Publisher
AIS
City or Country
Atlanta, GA
Citation
CHEN, Ang; NAH, Fiona Fui-hoon; and CHEN, Langtao.
Assessing classical and expressive aesthetics of web pages using machine learning. (2018). Midwest Association for Information Systems Conference, St. Louis, Missouri, May 2018. 1-3.
Available at: https://ink.library.smu.edu.sg/sis_research/10045
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://aisel-aisnet-org.libproxy.smu.edu.sg/mwais2018/33