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    Assessing User Interface Aesthetics based on the Inter-subjectivity of Judgment

    HCI 2016 - Fusion!

    Proceedings of the 30th International BCS Human Computer Interaction Conference (HCI 2016)

    Bournemouth University, Poole, UK, 11 - 15 July 2016


    Mathieu Zen & Jean Vanderdonckt



    "How to assess user interface aesthetics?" remains a question faced by many user interface researchers and designers during the user interface development life cycle since aesthetics positively influence usability, user experience, pleasureability, and trust. Visual techniques borrowed from visual design suggest that the graphical user interface layout could be assessed by aesthetic metrics such as balance, symmetry, proportion, regularity, and simplicity, to name a few. Whereas different formulas exist for computing each aesthetic metric and different interpretations to sum up their results, no consensus exists today on how to consistently evaluate these metrics in a way that is aligned with human judgement, which is intrinsically subjective.

    In order to address the challenging alignment of human subjectivity with machine objectivity, this paper reports on an experiment comparing the results issued from the inter-subjectivity of judgment of fifteen participants evaluating four main aesthetic metrics on a sample of ten graphical user interfaces and the values of these metrics calculated semi-automatically by a web-based application. The experiment suggests that some metrics, e.g. symmetry, proportion, simplicity, as computed from the formula are actually positively correlated with human judgment, while some other metrics, such as balance, are surprisingly not correlated with the formula computed, thus indicating that another formula or another interpretation should be determined. Therefore, a new formula for computing balance is defined that decomposes balance into horizontal and vertical balances which re-establish a correlation. This paper then provides some new insights on how to rely on these aesthetic metrics and other related metrics, whether they are interpreted manually or computed automatically.


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