Leveraging Mobile App Classification and User Context Information for Improving Recommendation Systems

Mobile apps play a significant role in current online environments where there is an overwhelming supply of information. Although mobile apps are part of our daily routine, searching and finding mobile apps is becoming a nontrivial task due to the current volume, velocity and variety of information. Therefore, app recommender systems provide users’ desired apps based on their preferences. However, current recommender systems and their underlying techniques are limited in effectively leveraging app classification schemes and context information. In this thesis, I attempt to address this gap by proposing a text analytics framework for mobile app recommendation by leveraging an app classification scheme that incorporates the needs of users as well as the complexity of the user-item-context information in mobile app usage pattern. In this recommendation framework, I adopt and empirically test an app classification scheme based on textual information about mobile apps using data from Google Play store. In addition, I demonstrate how context information such as user social media status can be matched with app classification categories using tree-based and rule-based prediction algorithms. Methodology wise, my research attempts to show the feasibility of textual data analysis in profiling apps based on app descriptions and other structured attributes, as well as explore mechanisms for matching user preferences and context information with app usage categories. Practically, the proposed text analytics framework can allow app developers reach a wider usage base through better understanding of user motivation and context information

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

Government Transparency: Six Strategies for More Open and Participatory Government

Offers strategies for realizing Knight's 2009 call for e-government and openness using Web 2.0 and 3.0 technologies, including public-private partnerships to develop applications, flexible procurement procedures, and better community broadband access

The simpler, the better? Presenting the COPING Android permission-granting interface for better privacy-related decisions

One of the great innovations of the modern world is the Smartphone app. The sheer multitude of available apps attests to their popularity and general ability to satisfy our wants and needs. The flip side of the functionality these apps offer is their potential for privacy invasion. Apps can, if granted permission, gather a vast amount of very personal and sensitive information. App developers might exploit the combination of human propensities and the design of the Android permission-granting interface to gain permission to access more information than they really need. This compromises personal privacy. The fact that the Android is the globally dominant phone means widespread privacy invasion is a real concern. We, and other researchers, have proposed alternatives to the Android permission-granting interface. The aim of these alternatives is to highlight privacy considerations more effectively during app installation: to ensure that privacy becomes part of the decision-making process. We report here on a study with 344 participants that compared the impact of a number of permission-granting interface proposals, including our own (called the COPING interface — COmprehensive PermIssioN Granting) and two Android interfaces. To conduct the comparison we carried out an online study with a mixed-model design. Our main finding is that the focus in these interfaces ought to be on improving the quality of the provided information rather than merely simplifying the interface. The intuitive approach is to reduce and simplify information, but we discovered that this actually impairs the quality of the decision. Our recommendation is that further investigation is required in order to find the “sweet spot” where understandability and comprehensiveness are maximised

Regulating Habit-Forming Technology

Tech developers, like slot machine designers, strive to maximize the user’s “time on device.” They do so by designing habit-forming products— products that draw consciously on the same behavioral design strategies that the casino industry pioneered. The predictable result is that most tech users spend more time on device than they would like, about five hours of phone time a day, while a substantial minority develop life-changing behavioral problems similar to problem gambling. Other countries have begun to regulate habit-forming tech, and American jurisdictions may soon follow suit. Several state legislatures today are considering bills to regulate “loot boxes,” a highly addictive slot-machine- like mechanic that is common in online video games. The Federal Trade Commission has also announced an investigation into the practice. As public concern mounts, it is surprisingly easy to envision consumer regulation extending beyond video games to other types of apps. Just as tobacco regulations might prohibit brightly colored packaging and fruity flavors, a social media regulation might limit the use of red notification badges or “streaks” that reward users for daily use. It is unclear how much of this regulation could survive First Amendment scrutiny; software, unlike other consumer products, is widely understood as a form of protected “expression.” But it is also unclear whether well-drawn laws to combat compulsive technology use would seriously threaten First Amendment values. At a very low cost to the expressive interests of tech companies, these laws may well enhance the quality and efficacy of online speech by mitigating distraction and promoting deliberation

Mining app reviews to support software engineering

The thesis studies how mining app reviews can support software engineering. App reviews —short user reviews of an app in app stores— provide a potentially rich source of information to help software development teams maintain and evolve their products. Exploiting this information is however difficult due to the large number of reviews and the difficulty in extracting useful actionable information from short informal texts. A variety of app review mining techniques have been proposed to classify reviews and to extract information such as feature requests, bug descriptions, and user sentiments but the usefulness of these techniques in practice is still unknown. Research in this area has grown rapidly, resulting in a large number of scientific publications (at least 182 between 2010 and 2020) but nearly no independent evaluation and description of how diverse techniques fit together to support specific software engineering tasks have been performed so far. The thesis presents a series of contributions to address these limitations. We first report the findings of a systematic literature review in app review mining exposing the breadth and limitations of research in this area. Using findings from the literature review, we then present a reference model that relates features of app review mining tools to specific software engineering tasks supporting requirements engineering, software maintenance and evolution. We then present two additional contributions extending previous evaluations of app review mining techniques. We present a novel independent evaluation of opinion mining techniques using an annotated dataset created for our experiment. Our evaluation finds lower effectiveness than initially reported by the techniques authors. A final part of the thesis, evaluates approaches in searching for app reviews pertinent to a particular feature. The findings show a general purpose search technique is more effective than the state-of-the-art purpose-built app review mining techniques; and suggest their usefulness for requirements elicitation. Overall, the thesis contributes to improving the empirical evaluation of app review mining techniques and their application in software engineering practice. Researchers and developers of future app mining tools will benefit from the novel reference model, detailed experiments designs, and publicly available datasets presented in the thesis

‘Stick them to the cross’:Anti-trafficking apps and the production of ignorance

There is a long history of ignorance production around trafficking in human beings. A proliferation of anti-trafficking apps plays an important role in the reinforcement of this ignorance. Anti-trafficking apps work in different ways to other (mis)information tools, but there is a lack of academic research on the topic. This paper addresses this gap through an agnotological approach: focusing on how ignorance is produced and becomes productive, rather than seeing ignorance as just a lack of knowledge. We investigate how anti-trafficking apps are used to manipulate (mis)understandings of and responses to human trafficking by enabling new types of awareness raising, user participation and ignorance production. The networking of ignorance that this allows – and the integration of this into new aspects of everyday life – illustrates de Goede’s (2012) warning that “the network is problematic as a security technique…because, ultimately, it has no outside” (p. 228)

Trans- and intra- apps: innovating the app market and use

This book provides an in-depth analysis of the challenges, potential and theoretical possibilities of apps and considers the processes of change for education and home learning environments