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Nowadays the app-in-app paradigm is becoming increasingly popular, and sub-apps have become an important form of mobile applications. WeChat, the leading app-in-app platform, provides millions of sub-apps that can be used for online…
Persuasive designs become prevalent on smartphones, and an increasing number of users report having problematic smartphone use behaviours. Persuasive designs in smartphones might be accountable for the development and reinforcement of such…
Mobile gaming apps are woven into children's daily lives. Given their ongoing cognitive and emotional development, children are especially vulnerable and depend on designs that safeguard their well-being. When apps feature manipulative…
Graphical User Interfaces (GUIs) are the primary means by which users interact with mobile applications, making them crucial to both app functionality and user experience. However, a major challenge in automated testing is the frequent…
Mobile gaming apps increasingly rely on third-party Software Development Kits SDKs for advertising, analytics, attribution, and user engagement, potentially introducing privacy exposure beyond traditional permission based risks. Existing…
As a new format of mobile application, mini programs, which function within a larger app and are built with HTML, CSS, and JavaScript web technology, have become the way to do almost everything in China. This paper presents our research on…
It is well known that learning customers' preference and making recommendations to them from today's information-exploded environment is critical and non-trivial in an on-line system. There are two different modes of recommendation systems,…
Current approaches for points-of-interest (POI) recommendation learn the preferences of a user via the standard spatial features such as the POI coordinates, the social network, etc. These models ignore a crucial aspect of spatial mobility…
Mobile applications (apps) have become deeply personal, constantly demanding access to privacy-sensitive information in exchange for more personalized user experiences. Such privacy-invading practices have generated major multidimensional…
POI recommendation is a key task in tourism information systems. However, in contrast to conventional point of interest (POI) recommender systems, the available data is extremely sparse; most tourist visit a few sightseeing spots once and…
We propose Secure Pick Up (SPU), a convenient, lightweight, in-device, non-intrusive and automatic-learning system for smartphone user authentication. Operating in the background, our system implicitly observes users' phone pick-up…
Current smartphone operating systems regulate application permissions by prompting users on an ask-on-first-use basis. Prior research has shown that this method is ineffective because it fails to account for context: the circumstances under…
In this paper we present the first population-level, city-scale analysis of application usage on smartphones. Using deep packet inspection at the network operator level, we obtained a geo-tagged dataset with more than 6 million unique…
Deceptive patterns, dark patterns, and manipulative user interfaces (UI) are a widely used design strategy that manipulates users to act against their own interests in pursuit of shareholder aims. These patterns may particularly affect…
Previous work has investigated the particularities of security practices within specific user communities defined based on country of origin, age, prior tech abuse, and economic status. Their results highlight that current security…
Deceptive patterns (DPs) are user interface designs deliberately crafted to manipulate users into unintended decisions, often by exploiting cognitive biases for the benefit of companies or services. While numerous studies have explored ways…
The super app paradigm, exemplified by platforms such as WeChat and AliPay, has revolutionized the mobile app landscape by enabling third-party developers to deploy add-ons within these apps. These add-ons, known as miniapps, leverage user…
Point-of-Interest (POI) recommender systems provide personalized recommendations to users and help businesses attract potential customers. Despite their success, recent studies suggest that highly data-driven recommendations could be…
As mobile app usage continues to rise, so does the generation of extensive user interaction data, which includes actions such as swiping, zooming, or the time spent on a screen. Apps often collect a large amount of this data and claim to…
This paper sets out a process of app analysis intended to support understanding of use but also redesign. From usage logs we infer activity patterns - Markov models - and employ probabilistic formal analysis to ask questions about the use…