Comparative Study of Icon Design for Mobile Application

Kamarulzaman, Nor Azura; Fabil, Norasikin; Zaki, Zulkifly Mohd; Ismail, Roesnita

doi:10.1088/1742-6596/1551/1/012007

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…While usability is broadly defined [KK95, Tra18, Tra20], icon usability is predominantly linked to the icon's ability to convey its meaning and the users' ability to comprehend it. Previous research highlights features such as visual complexity, semantic distance, and familiarity as major influences on icon usability [MCdB99, MCdB01, MI09, IMC07, SM14, KFZI20, SJ16, SKJ17]. These features are often operationally defined through user ratings or rankings on various scales (e.g., the perceived closeness between an icon and its represented information or the perceived aesthetics of icons) [MCdB01, MI09, IMC07, SJ16].…”

Section: Related Workmentioning

confidence: 99%

EvIcon: Designing High‐Usability Icon with Human‐in‐the‐loop Exploration and IconCLIP

Shen,

Cherng,

Igarashi

et al. 2023

Computer Graphics Forum

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Interface icons are prevalent in various digital applications. Due to limited time and budgets, many designers rely on informal evaluation, which often results in poor usability icons. In this paper, we propose a unique human‐in‐the‐loop framework that allows our target users, that is novice and professional user interface (UI) designers, to improve the usability of interface icons efficiently. We formulate several usability criteria into a perceptual usability function and enable users to iteratively revise an icon set with an interactive design tool, EvIcon. We take a large‐scale pre‐trained joint image‐text embedding (CLIP) and fine‐tune it to embed icon visuals with icon tags in the same embedding space (IconCLIP). During the revision process, our design tool provides two types of instant perceptual usability feedback. First, we provide perceptual usability feedback modelled by deep learning models trained on IconCLIP embeddings and crowdsourced perceptual ratings. Second, we use the embedding space of IconCLIP to assist users in improving icons' visual distinguishability among icons within the user‐prepared icon set. To provide the perceptual prediction, we compiled IconCEPT10K, the first large‐scale dataset of perceptual usability ratings over 10,000 interface icons, by conducting a crowdsourcing study. We demonstrated that our framework could benefit UI designers' interface icon revision process with a wide range of professional experience. Moreover, the interface icons designed using our framework achieved better semantic distance and familiarity, verified by an additional online user study.

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Section: Related Workmentioning

confidence: 99%

EvIcon: Designing High‐Usability Icon with Human‐in‐the‐loop Exploration and IconCLIP

Shen,

Cherng,

Igarashi

et al. 2023

Computer Graphics Forum

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“…Gambar 6. Key Element Icon (Sumber: Kamarulzaman et al, 2020) Berikut merupakan hasil dari setiap partisipan:…”

Section: Iconographyunclassified

Kajian Rujukan Tampilan Antarmuka Aplikasi E-Commerce Untuk Lansia

Meilian

Anwari

2022

ULTIMART

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Perkembangan teknologi yang pesat tidak dapat diikuti dengan baik oleh semua golongan usia di masyarakat, salah satunya adalah golongan lansia. Padahal perkembangan teknologi memiliki manfaat yang besar untuk menunjang kualitas hidup golongan lansia, salah satunya adalah aplikasi e-commerce. Sangat disayangkan dalam penggunaannya banyak dari golongan lansia yang merasa kurang kompeten untuk berurusan dengan teknologi, terutama dalam kaitan dengan tampilan antarmuka pada aplikasi e-commerce. Berupaya untuk mendalami pengalaman dari pengguna golongan usia lansia dalam perihal tampilan antarmuka pada aplikasi e-commerce. Serangkaian hasil analisis diimplementasikan ke dalam rancangan rujukan desain interface disesuaikan dengan pengalaman dari pengguna golongan lansia yang belum diungkapkan secara spesifik pada penelitian lain. Temuan yang diungkapkan dalam analisis penelitian diharapkan dapat meningkatkan efektivitas kemudahan penggunaan aplikasi e-commerce yang ditujukan untuk pengguna golongan lansia. Kata Kunci: tampilan antarmuka; lansia; E-commerce; rujukan desain.

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“…This could be a future research direction to study a possible correlation between some specific icon visual features and tendency of some age groups to download this game. Kamarulzaman et al (2020) in [23] carried a comparative study on icon design for mobile applications. They analyzed color, semantics, uniqueness, and concreteness elements.…”

Section: Related Workmentioning

confidence: 99%

Mobile games success and failure: mining the hidden factors

Kerim

Genç

2022

Neural Comput & Applic

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Predicting the success of a mobile game is a prime issue in game industry. Thousands of games are being released each day. However, a few of them succeed while the majority fail. Toward the goal of investigating the potential correlation between the success of a mobile game and its specific attributes, this work was conducted. More than 17 thousand games were considered for that reason. We show that IAPs (In-App Purchases), genre, number of supported languages, developer profile, and release month have a clear effect on the success of a mobile game. We also develop a novel success score reflecting multiple objectives. Furthermore, we show that game icons with certain visual characteristics tend to be associated with more rating counts. We employ different machine learning models to predict a novel success score metric of a mobile game given its attributes. The trained models were able to predict this score, as well as the expected rating average and rating count for a mobile game with 70% accuracy.

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Comparative Study of Icon Design for Mobile Application

Cited by 6 publications

References 20 publications

EvIcon: Designing High‐Usability Icon with Human‐in‐the‐loop Exploration and IconCLIP

EvIcon: Designing High‐Usability Icon with Human‐in‐the‐loop Exploration and IconCLIP

Kajian Rujukan Tampilan Antarmuka Aplikasi E-Commerce Untuk Lansia

Mobile games success and failure: mining the hidden factors

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