Computational Model for Webpage Aesthetics using SVM

Ranjan Maity,Samit K Bhattacharya

doi:10.14236/ewic/hci2017.8

Abstract

Computational model for webpage aesthetics prediction helps designer to determine usability and to improve it. It has been reported that positional geometry of the webpage objects are primarily important for aesthetics computation. In this paper, we propose a computational model for predicting webpage aesthetics based on the positional geometry features of webpage objects. We have considered the best known 13 features that affect aesthetics. By varying these 13 features, we have designed 52 interfaces and rated them by 100 users in a 5 point Likerts scale. Our 1 dimensional ANOVA study on users rating shows, 9 out of the 13 features are important for webpage aesthetics. Based on these 9 features, we created a computational model for webpage aesthetics prediction. Our computational model works based on Support Vector Machine (SVM). To judge the efficacy of our model, we considered 10 popular webpages, and got them rated by 80 users. Experimental results show that our computational model can predict webpage aesthetics with an accuracy of 90%.

Highlights

With the advancement of technology, electronic devices like mobiles, laptops, i-pads etc. have become an essential part in our daily life
It is argued that aesthetically pleasing interface increase user efficiency and decrease perceived interface complexity, which in turn helps in increasing usability, productivity and acceptability
Ngo et al (2003) claimed that the order value may be a measure for aesthetics computation

Summary

Introduction

With the advancement of technology, electronic devices like mobiles, laptops, i-pads etc. have become an essential part in our daily life. Ngo et al (2003) reported that positions of rectangular webpage objects in a layout are primarily important for aesthetics computation. Contents of webpages objects seem no impact on aesthetics They proposed a computational model for webpage aesthetics based on the 13 positional geometry features of webpage objects. The average of these feature values (termed as order) was used to judge the aesthetics of a webpage. ANOVA study on the users’ ratings revealed only 9 out of the 13 features are important for aesthetics measurement Based on those 9 features, we developed a computational model to predict webpage aesthetics.

Methods

Results

Conclusion