A Computational Model to Predict Aesthetic Quality of Text Elements of GUI

Maity, Ranjan; Madrosiya, Akshay; Bhattacharya, Samit

doi:10.1016/j.procs.2016.04.081

Cited by 10 publications

(13 citation statements)

References 19 publications

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“…But in some studies we observed that contents of webpage elements have impact on aesthetics. Our model may be combined with the models of short animations [14], text [10] and image model [9] to develop a complete computational model for evaluating aesthetic quality of a webpage. In our work, we consider the 4 variations of each feature.…”

Section: Resultsmentioning

confidence: 99%

A Model to Compute Webpage Aesthetics Quality Based on Wireframe Geometry

Maity

Bhattacharya

2017

Human-Computer Interaction – INTERACT 2017

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Computational models of web page aesthetics prediction are useful for the designers to determine the usability and to improve it. Positional geometry of webpage objects (wireframe) is an important factor for determining the webpage aesthetics as shown in studies. In this paper, we propose a computational model for predicting webpage aesthetics based on the positional geometry. We have considered 13 features of positional geometry that affect aesthetics, as reported in literature. By varying these 13 features, we have designed 52 interfaces' wireframes and rated them by 100 users in a 5 point rating 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' wireframes, and got them rated by 80 users. Experimental results show that our computational model can predict webpage aesthetics with an accuracy of 90%.

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Section: Resultsmentioning

confidence: 99%

A Model to Compute Webpage Aesthetics Quality Based on Wireframe Geometry

Maity

Bhattacharya

2017

Human-Computer Interaction – INTERACT 2017

Self Cite

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“…Classical aesthetics seem to be perceived more evenly by users, while expressive aesthetics are denounced by more dispersion depending on contextual stimuli (Mahlke and Thüring 2007). Aesthetic value of graphical user interfaces has been attempted to measure objectively by several geometry-related and image-related metrics, e.g., balance, equilibrium, symmetry and sequences well as color contrast and saturation to avoid human involvement in the process (Maity et al 2015(Maity et al , 2016Ngo et al 2000Ngo et al , 2001Ngo et al , 2003Vanderdonckt and Gillo 1994;Vanderdonckt 2014, 2016). These visual techniques in the arrangement of layout components can be divided into physical techniques, composition techniques, association and disassociation techniques, ordering techniques, as well as photographic techniques (Vanderdonckt and Gillo 1994).…”

Section: Measuring Visual Qualities Of Graphical User Interfacesmentioning

confidence: 99%

“…Aesthetics considerations in computers and other devices have quickly started to garner attention as the means to positively affect usability and satisfaction (Ahmed et al 2009;Maity et al 2015Maity et al , 2016Norman 2004;Tractinsky et al 2000). Studies have shown that a user interface with balanced elements promotes user engagement, while a cluttered interface may result in frustration (Jankowski et al 2016(Jankowski et al , 2019Lee and Boling 1999;Ngo et al 2000;Salimun et al 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Prior literature (Maity et al 2015(Maity et al , 2016Zen and Vanderdonckt 2016) suggests that contradictory results in metric-based evaluation theories and tools of aesthetics in GUI research are perhaps caused by analyzing user interfaces as entities without considering the content. This gap in calculating aesthetics with metric-based evaluations means that many metric evaluations consider a graphical user interface as a single piece although it essentially consists of different elements with specific purposes and designs (Maity et al 2015).…”

mentioning

confidence: 99%

“…This gap in calculating aesthetics with metric-based evaluations means that many metric evaluations consider a graphical user interface as a single piece although it essentially consists of different elements with specific purposes and designs (Maity et al 2015). For instance, designing an interactive button is very different from defining type faces in that these elements serve different purposes in user interfaces (Maity et al 2016). Moreover, empirical studies on GUI aesthetics have often relied on website layouts as study objects (Hassenzahl 2004).…”

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confidence: 99%

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Development of measurement instrument for visual qualities of graphical user interface elements (VISQUAL): a test in the context of mobile game icons

Jylhä

Hamari

2020

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Graphical user interfaces are widely common and present in everyday human–computer interaction, dominantly in computers and smartphones. Today, various actions are performed via graphical user interface elements, e.g., windows, menus and icons. An attractive user interface that adapts to user needs and preferences is progressively important as it often allows personalized information processing that facilitates interaction. However, practitioners and scholars have lacked an instrument for measuring user perception of aesthetics within graphical user interface elements to aid in creating successful graphical assets. Therefore, we studied dimensionality of ratings of different perceived aesthetic qualities in GUI elements as the foundation for the measurement instrument. First, we devised a semantic differential scale of 22 adjective pairs by combining prior scattered measures. We then conducted a vignette experiment with random participant (n = 569) assignment to evaluate 4 icons from a total of pre-selected 68 game app icons across 4 categories (concrete, abstract, character and text) using the semantic scales. This resulted in a total of 2276 individual icon evaluations. Through exploratory factor analyses, the observations converged into 5 dimensions of perceived visual quality: Excellence/Inferiority, Graciousness/Harshness, Idleness/Liveliness, Normalness/Bizarreness and Complexity/Simplicity. We then proceeded to conduct confirmatory factor analyses to test the model fit of the 5-factor model with all 22 adjective pairs as well as with an adjusted version of 15 adjective pairs. Overall, this study developed, validated, and consequently presents a measurement instrument for perceptions of visual qualities of graphical user interfaces and/or singular interface elements (VISQUAL) that can be used in multiple ways in several contexts related to visual human-computer interaction, interfaces and their adaption.

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Antecedents of Usability to Sustain Users’ Engagement in Online Learning

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2024

The Palgrave Handbook of Sustainable Digitalization for Business, Industry, and Society

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A Computational Model to Predict Aesthetic Quality of Text Elements of GUI

Cited by 10 publications

References 19 publications

A Model to Compute Webpage Aesthetics Quality Based on Wireframe Geometry

A Model to Compute Webpage Aesthetics Quality Based on Wireframe Geometry

Development of measurement instrument for visual qualities of graphical user interface elements (VISQUAL): a test in the context of mobile game icons

Antecedents of Usability to Sustain Users’ Engagement in Online Learning

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