The research scope and questions of this thesis ought to be set and clarified before proceeding with the presentation of the research work. This will clarify its contri- butions within the areas of Adaptive User Interfaces, User Modelling and Personal- isation. The thesis aims to extend the state-of-the-art paradigm in news personalisa- tion, which primarily focuses on news content recommendation, by developing user interface personalisation in news app interfaces. In particular, “contemporary mo- bile news apps offer personalised news content recommendations and/or the ability to manually customise their user interfaces. The scope, however, of news person- alisation needs to extend beyond what content users access and read to how that content is delivered, presented, and consumed.”
To address the high-level goal of this thesis requires an investigation of four research questions (RQ1-RQ4). The thesis is organised around the four RQs and the methodology followed to examine each question is provided below.
RQ1: How do people vary in accessing and reading the news on smartphones? What are the stereotypical news readers profiles?
RQ2: How can smartphones news apps detect and learn individual user’s news reading patterns of interactions?
RQ3: How can smartphone news apps exploit a news reader profile to adapt the interface and the interaction?
1.2. Research Scope and Questions 7 app? To what extent the user interface personalisation is beneficial to different kinds of news reading behaviour?
RQ1 is addressed in Chapter 3, which focuses on understanding news reading behaviour in order to reveal people’s differences whilst reading the news on mobile devices. While many prior research works (Pew Research Centre, 2012; Reuters Institute, 2014; Fortunati et al., 2014; American Press Institute, 2014) have investi- gated users’ news interests by examining, for example, socio-political factors, per- sonality traits and so forth, no prior work, to the best of the author’s knowledge, has been conducted in relation to the stereotypical behaviour of accessing and con- suming the news. The study, therefore, presented in Chapter 3 does not attempt to repeat previous works, rather it focuses on patterns of interaction behaviour in rela- tion to how users interact with mobile news apps interfaces to access and consume the news content. For example, it examines how people search through news head- lines and choose articles to read and how they read the text of selected articles. The study utilises a survey method, in which participants responded in an online ques- tionnaire aiming to investigate those news consumption behaviour differences. The results of the study serve as the foundation for defining a News Reader Typology for mobile news apps consumption. The typology describes three different kinds of news consumption behaviour, namely as ‘Trackers’, ‘Reviewers’ and ‘Dippers’, and defines their characteristics. Statistical methods and an unsupervised clustering technique were used to form the typology and devise the definitions of the different kinds of news reading behaviour. It is important to note that the proposed News Reader Typology was utilised as the basis to explore the other research questions.
RQ2 is addressed in Chapter 5. Chapter 5 describes the User Modelling (UM) component and data collections through a dedicated news app, called Habito News. Both the UM component and the news app are part of the adaptive news research platform introduced in Chapter 4. Chapter 5 introduces models that learn to de- tect user’s interaction behaviour patterns. It proposes a hierarchical framework for analysing mobile news reading interactions and explores two approaches of user model acquisition. Unlike previous research works that focused on modelling users’
news reading interests, the two approaches attempt to model users’ news reader type and users’ news reading interaction factors, as originate from the News Reader Typology. It presents a descriptive statistical analysis on the interaction corpus col- lected with deployments of Habito News app through the Google Play platform and explains the implementation of machine learning algorithms utilised in the learning process.
RQ3 is addressed in Chapter 6 wherein the design space of variant user inter- face designs and interactions that would suit different kinds of news reading be- haviour is explored. An iterative process for the design of user interface features was adopted and the Chapter reports the findings of two controlled laboratory stud- ies (i.e., Phase I and Phase II) that aimed to assess the usability, user experience and satisfaction of different forms of Habito News user interface. User interface features were designed using Justinmind7, a wireframe prototyping tool. Qualita- tive and quantitative methods were used to gather user’s data during the two studies. The Chapter also introduces the Adaptation Mechanism (AM), another component discussed in Chapter 4, the component that is responsible to generate UI designs on-the-fly and adapt the user interface of Habito News.
RQ4 is addressed in Chapter 7. This Chapter puts together all the research strands discussed in Chapters 3, 4, 5, 6 and reports the results of a field evalua- tion study of Habito News, which aims to examine the effectiveness of automatic adaptation in news apps interfaces. The Chapter presents a layered evaluation study(Paramythis et al., 2010; Brusilovsky et al., 2001) in which the interaction assessment layer (i.e., user model acquisition) and the adaptation decision-making layer (i.e., adaptation mechanism and variant user interfaces of the news app) are examined. Qualitative data was collected through a daily email questionnaire and the AttrakDiff (Hassenzahl et al., 2003) questionnaire that administered twice be- fore and after the adaptation. AttrakDiff measured user satisfaction and experi- ence in four dimensions as follows: Pragmatic quality (PQ) measures the support for achieving a goal; hedonic quality stimulation (HQ-S) measures the perceived
1.3. Thesis Contributions 9