Empirical assessment and improvement of ubiquitous notifications

Abstract

Smart devices have become ubiquitous. Devices like smartphones, smartwatches, tablets, laptops, and smart TVs accompany us throughout the day. Advancements in computational efficiency and wireless technologies allow these devices to be always on and always connected. While some devices are used situationally, other devices like smartphones are always with the user. This inherently changed how we interact with these devices. Instead of manually looking for news and new messages, these devices can proactively inform us about new events through notifications around the clock. From new messages, reminders, to system updates, notifications are fundamentally personal and cover a wide range of topics. While notifications are valued by users and make them feel connected, they can also cause interruptions and distractions. With more and more services making use of notifications on more and more devices, potential adverse effects are amplified. For instance, a single email might alert a user on multiple devices using multiple modalities. To reduce adverse effects, an understanding of different categories of notifications, different devices, and user needs is required. Notification management is a balancing act between satisfying users' information needs and respecting their attention. This thesis investigates the empirical assessment and improvements of ubiquitous notifications. We present multiple user studies, from online surveys, lab studies, in-situ studies to large-scale in-the-wild studies. We first focus on the assessment and management of mobile notifications on smartphones, tackling the challenges of conducting in-situ controlled and in-the-wild user studies while preserving the users' privacy. We present a notification data set, propose user types, and introduce new approaches for users to reflect on and manage their notifications. We then expand the scope to include other device types such as smartwatches, tablets, and laptops to create a holistic understanding of how these devices differ regarding user expectations for receiving notifications by combining activity logging on multiple devices with experience sampling. Afterward, we expand the scope again to include large and pervasive displays. Finally, we present an open-source logging framework for mobile devices to enable other developers and researchers to build on top of this work. The contribution of this thesis is threefold. First, this thesis introduces multiple approaches to conducting research on ubiquitous notifications, from controlled lab studies to large-scale in-the-wild studies. Second, the thesis provides insights into users' notification preferences and interactions on different types of devices. Third, a technical contribution, including an open-source notification logging framework and notification data set. These contributions are a foundation for future research on ubiquitous notifications.