The Digital Architectures of Social Media: Comparing Political Campaigning on Facebook, Twitter, Instagram, and Snapchat in the 2016 U.S. Election

The present study argues that political communication on social media is mediated by a platform's digital architecture, defined as the technical protocols that enable, constrain, and shape user behavior in a virtual space. A framework for understanding digital architectures is introduced, and four platforms (Facebook, Twitter, Instagram, and Snapchat) are compared along the typology. Using the 2016 US election as a case, interviews with three Republican digital strategists are combined with social media data to qualify the studyies theoretical claim that a platform's network structure, functionality, algorithmic filtering, and datafication model affect political campaign strategy on social media

Towards ad-hoc situation determination

Toolkits such as PlaceLab [1] have been successful in making location information freely available for use in experimental ubiquitous computing applications. As users' expectations of ubiquitous computing applications grow, we envisage a need for tools that can deliver a much richer set of contextual information. The high-level situation of the current environment is a key contextual element, and this position paper focuses on a method to provide this information for an ad-hoc group of people and devices. The contributions of this paper are i) a demonstration of how information retrieval (IR) techniques can be applied to situation determination in context-aware systems, ii) a proposal of a novel approach to situation determination that combines these adapted IR techniques with a process of cooperative interaction, and iii) a report of preliminary results. The approach offers a high level of utility and accuracy, with a greater level of automation than other contemporary approaches

General characteristics of anticipated user experience (AUX) with interactive products

Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process

Analyzing the Use of Camera Glasses in the Wild

Camera glasses enable people to capture point-of-view videos using a common accessory, hands-free. In this paper, we investigate how, when, and why people used one such product: Spectacles. We conducted 39 semi-structured interviews and surveys with 191 owners of Spectacles. We found that the form factor elicits sustained usage behaviors, and opens opportunities for new use-cases and types of content captured. We provide a usage typology, and highlight societal and individual factors that influence the classification of behaviors.Comment: In Proceedings of the 37th Annual ACM Conference on Human Factors in Computing Systems (CHI 2019). ACM, New York, NY, US