Data-Driven Approaches to Modeling User Perception Towards Mobile User Interface

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Data-Driven Approaches to Modeling User Perception Towards Mobile 
User Interface"

By

Mr. Ziming WU


Abstract

Mobile User Interface (UI) serves as a major window where the 
communication between users and mobile applications happens. It not only 
defines the look and feel of an app but also plays a key role in creating 
good interactive experience with the installed functions and contents for 
users. While designers strike to craft a good UI, a potential gap between 
designers’ intention and users’ perceived quality of the design might 
appear. Therefore, understanding how users perceive the UI design, e.g., 
the perceived usability and aesthetics, is crucial for designers to 
reflect on and reshape their products for better user experience. It 
requires designers to frequently elicit feedback from target users and/or 
domain experts during the iterative app design process. Although deemed 
effective, this approach is resource-intensive. In contrast, this thesis 
explores the use of data-driven methods to model user perception towards 
mobile UI design and further support the generation of more usable UI. We 
first propose a prediction model to infer the perceived brand personality 
of mobile apps from their static UI pages. In particular, we compile a set 
of color-based, texture-based, and organization-based visual descriptors 
of UI pages and demonstrate their promising predictive power with a 
non-linear prediction model on a collected dataset. The results can 
benefit designers by highlighting contributing graphical factors to brand 
personality creation. Next, to analyze the dynamic UI changes, i.e., 
mobile UI animation, we introduce a two-stream deep neural network to 
model the user engagement with UI animation, which shows a reasonable 
accuracy. Based on the features encoded by the model, we further derive 
the potential design issues of animation to inform design improvement. We 
develop a prototype AniLens and evaluate it with professional designers. 
Finally, we investigate how computational powers can aid designers in 
generating more user-friendly mobile UI. We leverage online curation data 
to generate the perceived semantics of color filters. Our results indicate 
that the mobile UI of color filter applications incorporated with the 
derived semantics which is in line with users’ consensus, can achieve 
better user experience. In all, we demonstrate the reasonable 
effectiveness of our proposed data-driven methods in modeling user 
perception towards mobile UI and also provide insight into how they can be 
leveraged to facilitate UI generation. In the end, we conclude the thesis 
by sketching the future work on developing more supportive computational 
tools for mobile UI design.


Date:			Wednesday, 8 July 2020

Time:			10:00am - 12:00noon

Zoom Meeting:		https://hkust.zoom.us/j/95407702789

Chairman:		Prof. Man YU (ISOM)

Committee Members:	Prof. Xiaojuan MA (Supervisor)
   			Prof. Pedro SANDER
 			Prof. Chiew Lan TAI
 			Prof. Wenbo WANG (MARK)
 			Prof. Hongbo FU (CityU)


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