Health Vlogs as Social Support for Chronic Illness Management.

Studies have shown positive impact of video blogs (vlogs) on patient education. However, we know little on how patient-initiated vlogs shape the relationships among vloggers and viewers. We qualitatively analyzed 72 vlogs on YouTube by users diagnosed with HIV, diabetes, or cancer and 1,274 comments posted to the vlogs to understand viewers' perspectives on the vlogs. We found that the unique video medium allowed intense and enriched personal and contextual disclosure to the viewers, leading to strong community-building activities and social support among vloggers and commenters, both informationally and emotionally. Furthermore, the unique communication structure of the vlogs allowed ad hoc small groups to form, which showed different group behavior than typical text-based social media, such as online communities. We provide implications to the Health Care Industry (HCI) community on how future technologies for health vlogs could be designed to further support chronic illness management.

Health Vlogger-Viewer Interaction in Chronic Illness Management.

Health video blogs (vlogs) allow individuals with chronic illnesses to share their stories, experiences, and knowledge with the general public. Furthermore, health vlogs help in creating a connection between the vlogger and the viewers. In this work, we present a qualitative study examining the various methods that health vloggers use to establish a connection with their viewers. We found that vloggers used genres to express specific messages to their viewers while using the uniqueness of video to establish a deeper connection with their viewers. Health vloggers also explicitly sought interaction with their viewers. Based on these results, we present design implications to help facilitate and build sustainable communities for vloggers.

Co-located collaborative visual analytics around a tabletop display.

Co-located collaboration can be extremely valuable during complex visual analytics tasks. We present an exploratory study of a system designed to support collaborative visual analysis tasks on a digital tabletop display. Fifteen participant pairs employed Cambiera, a visual analytics system, to solve a problem involving 240 digital documents. Our analysis, supported by observations, system logs, questionnaires, and interview data, explores how pairs approached the problem around the table. We contribute a unique, rich understanding of how users worked together around the table and identify eight types of collaboration styles that can be used to identify how closely people work together while problem solving. We show how the closeness of teams' collaboration and communication influenced how they performed on the task overall. We further discuss the role of the tabletop for visual analytics tasks and derive design implications for future co-located collaborative tabletop problem solving systems.