A neural network-based approach for user experience assessment

Abstract

The objective of this study is to approximate the links between user satisfaction and its determinants without having the restrictions of common statistical procedures such as linearity, symmetry and normality. For this reason, artificial neural networks are utilised and trained with the observations of an extensive survey on user satisfaction with respect to website attributes. Each observation includes evaluations about the performance of 18 specific and 9 general website attributes as well as an evaluation about overall user satisfaction. The analysis results indicate that website attributes present different impacts on satisfaction whereas the relationships found feature both asymmetry and nonlinearity. Finally, function approximation using neural networks is found to be appropriate for estimating such kind of relationships providing valuable information about satisfaction's formation.

Keywords:

• user satisfaction
• experience assessment
• asymmetry
• nonlinearity
• neural networks