RANKING CONTENT SUGGESTIONS BASED ON CALENDAR DATA

Content suggestions can be ranked by using calendar data in addition to, for example, travel and map data. First, the system receives calendar data input from the user containing information such as business, leisure, and other activities scheduled to occur on certain dates and times. Then, the system receives travel data from the user. For example, the user might book a round trip flight to and from a certain city scheduled to occur on specific dates and times. The system then uses calendar data in addition to, for example, travel and map data to identify suggestions for lodging, dining, or other pertinent activities convenient for the user. Specifically, the improved process uses calendar data to signal, filter, and generate optimally ranked results based on the user\u27s specific location on a given date and time, making the search process more efficient and convenient for the user

Gaze and Gestures in Telepresence: multimodality, embodiment, and roles of collaboration

This paper proposes a controlled experiment to further investigate the usefulness of gaze awareness and gesture recognition in the support of collaborative work at a distance. We propose to redesign experiments conducted several years ago with more recent technology that would: a) enable to better study of the integration of communication modalities, b) allow users to freely move while collaborating at a distance and c) avoid asymmetries of communication between collaborators.Comment: Position paper, International Workshop New Frontiers in Telepresence 2010, part of CSCW2010, Savannah, GA, USA, 7th of February, 2010. http://research.microsoft.com/en-us/events/nft2010

Apps That Motivate: a Taxonomy of App Features Based on Self-Determination Theory

Nowadays, thousands of popular applications are designed to help users improve their lives through behavioural adjustment (e.g., meditate more, stay hydrated). However, our understanding of how certain design features align with constructs of behavior theories remain limited. We analyze 208 apps from the Apple App Store and identified 12 design features afforded by current tools that we classified according to the Self-Determination Theory. The taxonomy reported in this paper, we argue, provides a simple tool for designers to evaluate how specific features, and combination of features, may work to motivate users towards their desired goals. Additionally, the presented taxonomy is intended to help researchers test new interventions by discussing relevant research gaps

Annotations of maps in collaborative work at a distance

This thesis inquires how map annotations can be used to sustain remote collaboration. Maps condense the interplay of space and communication, solving linguistic references by linking conversational content to the actual places to which it refers. This is a mechanism people are accustomed to. When we are face-to-face, we can point to things around us. However, at a distance, we need to recreate a context that can help disambiguate what we mean. A map can help recreate this context. However other technological solutions are required to allow deictic gestures over a shared map when collaborators are not co-located. This mechanism is here termed Explicit Referencing. Several systems that allow sharing maps annotations are reviewed critically. A taxonomy is then proposed to compare their features. Two filed experiments were conducted to investigate the production of collaborative annotations of maps with mobile devices, looking for the reasons why people might want to produce these notes and how they might do so. Both studies led to very disappointing results. The reasons for this failure are attributed to the lack of a critical mass of users (social network), the lack of useful content, and limited social awareness. More importantly, the study identified a compelling effect of the way messages were organized in the tested application, which caused participants to refrain from engaging in content-driven explorations and synchronous discussions. This last qualitative observation was refined in a controlled experiment where remote participants had to solve a problem collaboratively, using chat tools that differed in the way a user could relate an utterance to a shared map. Results indicated that team performance is improved by the Explicit Referencing mechanisms. However, when this is implemented in a way that is detrimental to the linearity of the conversation, resulting in the visual dispersion or scattering of messages, its use has negative consequences for collaborative work at a distance. Additionally, an analysis of the eye movements of the participants over the map helped to ascertain the interplay of deixis and gaze in collaboration. A primary relation was found between the pair's recurrence of eye movements and their task performance. Finally, this thesis presents an algorithm that detects misunderstandings in collaborative work at a distance. It analyses the movements of collaborators' eyes over the shared map, their utterances containing references to this workspace, and the availability of "remote" deictic gestures. The algorithm associates the distance between the gazes of the emitter and gazes of the receiver of a message with the probability that the recipient did not understand the message

Revisiting the Design Agenda for Privacy Notices and Security Warnings

System-generated user-facing notices, dialogs, and warnings in privacy and security interventions present the opportunity to support users in making informed decisions about identified risks. However, too often, they are bypassed, ignored, and mindlessly clicked through, mainly in connection to the well-studied effect of user fatigue and habituation. The contribution of this position paper is to provide a summarized review of established and emergent design dimensions and principles to limit such risk-prone behavior, and to identify three emergent research and design directions for privacy-enhancing dialogs.Comment: 11 pages, 3 figures, Workshop on Privacy Interventions and Education (PIE): Encouraging Privacy Protective Behavioral Change Online, ACM CHI Conference on Human Factors in Computing Systems, 23-28 April 2023, Hamburg, German