Title: Mobile application user interface layout features for data-driven design

Authors: Zexun Jiang; Qincheng Gao; Yifan Wei; Hao Yin

Addresses: Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China ' International School, Beijing University of Posts and Telecommunications, Beijing, China ' International School, Beijing University of Posts and Telecommunications, Beijing, China ' Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China

Abstract: With the rapid development of mobile platforms and smart devices, mobile applications have grown into one of the massive online markets. To build a high-quality and popular mobile application, well-designed user interfaces are important. This work proposes quantitative features to analyse mobile interface layouts to support data-driven design, including consistency, hierarchy, contrast, balance and harmony. A neural deep learning model is developed based on these features to predict user ratings of applications. These features and the model are evaluated on an open dataset, and the results prove that they can be utilised to reliably study and optimise mobile user interface design.

Keywords: mobile application; user interface design; quantitative analysis.

DOI: 10.1504/IJES.2021.120255

International Journal of Embedded Systems, 2021 Vol.14 No.5, pp.421 - 431

Received: 20 Mar 2020
Accepted: 06 Apr 2020
Published online: 13 Jan 2022 *

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