Media is evolving from traditional linear narratives to personalised experiences, where control over information (or how it is presented) is given to individual audience members. Measuring and understanding audience engagement with this media is important in at least two ways: (1) a post-hoc understanding of how engaged audiences are with the content will help production teams learn from experience and improve future productions; (2), this type of media has potential for real-time measures of engagement to be used to enhance the user experience by adapting content on-the-fly. Engagement is typically measured by asking samples of users to self-report, which is time consuming and expensive. In some domains, however, interaction data have been used to infer engagement. Fortuitously, the nature of interactive media facilitates a much richer set of interaction data than traditional media; our research aims to understand if these data can be used to infer audience engagement. In this paper, we report a study using data captured from audience interactions with an interactive TV show to model and predict engagement. We find that temporal metrics, including overall time spent on the experience and the interval between events, are predictive of engagement. The results demonstrate that interaction data can be used to infer users' engagement during and after an experience, and the proposed techniques are relevant to better understand audience preference and responses.

The use of mobile devices during television viewing is now commonplace, and broadcasters are increasingly supplying programme-related ‘companion content’. To produce an optimal user experience, it is important to determine how the delivery of companion content affects and is perceived by the viewer — without this we risk distracting the viewer, leading to frustration and disengagement. We present a controlled study investigating how attention, cognitive load (as measured by the NASA TLX), and users’ preferences are affected by the provision of two different content delivery modes: pushed and pulled . We find that delivery mode affected the temporal distribution of gaze to the tablet, with a consistent viewing pattern for pushed updates, which attracted attention within a few seconds, and a more diverse set of viewing patterns when updates were pulled. Cognitive load was similar in both conditions, and there was no consensus as to which mode was preferred, but users showed strong, polarised individual preferences. The advantages of each delivery mode are presented as a set of recommendations for the delivery of companion content.

Nonlinear forms of diagrammatic presentation, such as node-arc graphs, are a powerful and elegant means of visual information presentation. Although providing nonvisual access is now routine for many forms of linear information, it becomes more difficult as the structure of the information becomes increasingly nonlinear. An understanding of the ways in which graphs benefit sighted people, based on experiments and the literature, together with the difficulties encountered when exploring graphs nonvisually, helps form a solution for nonvisual access to graphs. This article proposes that differing types of annotation offer a powerful and flexible technique for transferring the benefits of graph-based diagrams, as well as for reducing disorientation while moving around the graph and for tackling some of the inherent disadvantages of using sound. Different forms of annotation that may address these problems are explored, classified, and evaluated, including notes designed to summarise and to aid node differentiation. Graph annotation may be performed automatically, creating a graph that evaluation shows requires less mental effort to explore and on which tasks can be achieved more effectively and more efficiently.

Dynamic micro-content—interactive or updating widgets and features—is now widely used on the Web, but there is little understanding of how people allocate attention to it. In this article we present the results of an eye-tracking investigation examining how the nature of dynamic micro-content influences whether or not the user views it. We propose and validate the Dynamic Update Viewing-likelihood (DUV) model, a CHi-squared Automatic Interaction Detector (CHAID) model that predicts with around 80% accuracy whether users view dynamic updates as a function of how they are initiated, their size, and their duration. The model is constructed with data from live Web sites and does not rely on knowledge of the user's task to make its predictions, giving it a high level of external validity. We discuss one example of its application: informing how dynamic content should be presented in audio via assistive technology for people with visual impairments.

This paper describes the evaluation of software, software designed to allow visually impaired users to explore the structures of chemical molecules using a speech based presentation. Molecular structures are typically presented as two dimensional schematics, and are an important example of a widely used form of diagram -- the graph. software is designed for exploring this specific class of graph. Among its features is the ability to recognise and make explicit features of the graph that would otherwise need to be inferred. The evaluation compared software with a simpler version without this facility, and found that participants were able to explore molecular structures more easily. We discuss the software, evaluation and results, particularly comparing them with theoretical considerations about how sighted readers use diagrams. Finally, we extract the important issues for non-visual graph presentation: making implicit features explicit; enabling hierarchical and connection-based browsing; allowing annotation; and helping users keep their orientation.

One aspect of non-visual visualisation is providing accessibility to diagrams for users with visual impairments. In this paper, we review the literature on diagrams and non-visual presentation in order to elucidate the issues involved in making graph based diagrams accessible using speech and non-speech sound. First we examine the nature, scope and uses of these diagrams. We then describe the nature of diagrams: how do diagrams differ from other representations; how do sighted readers read, understand, and extract information from diagrams; what cognitive processes do diagrams facilitate; and what factors affect how diagrams may be understood? After a comparison of visual with aural presentation we discuss the work presented by others in this field, particularly looking at their reasons for implementing how they do in light of our examination of visual comprehension. The paper concludes with a discussion of how these issues combine and conflict to influence requirements for interface design.