Hyunggu Jung

'MASTerful' Matchmaking in Service Transactions: Inferred Abilities, Needs and Interests versus Activity Histories

Timebanking is a growing type of peer-to-peer service exchange, but is hampered by the effort of finding good transaction partners. We seek to reduce this effort by using a Matching Algorithm for Service Transactions (MAST). MAST matches transaction partners in terms of similarity of interests and complementarity of abilities and needs. We present an experiment involving data and participants from a real timebanking network, that evaluates the acceptability of MAST, and shows that such an algorithm can retrieve matches that are subjectively better than matches based on matching the category of peoples historical offers or requests to the category of a current transaction request.

A user modeling approach for reasoning about interaction sensitive to bother and its application to hospital decision scenarios

In this paper, we present a framework for interacting with users that is sensitive to the cost of bother and then focus on its application to decision making in hospital emergency room scenarios. We begin with a model designed for reasoning about interaction in a single-agent single-user setting and then expand to the environment of multiagent systems. In this setting, agents consider both whether to ask other agents to perform decision making and at the same time whether to ask questions of these agents. With this fundamental research as a backdrop, we project the framework into the application of reasoning about which medical experts to interact with, sensitive to possible bother, during hospital decision scenarios, in order to deliver the best care for the patients that arrive. Due to the real-time nature of the application and the knowledge-intensive nature of the decisions, we propose new parameters to include in the reasoning about interaction and sketch their usefulness through a series of examples. We then include a set of experimental results confirming the value of our proposed approach for reasoning about interaction in hospital settings, through simulations of patient care in those environments. We conclude by pointing to future research to continue to extend the model for reasoning about interaction in multiagent environments for the setting of time-critical care in hospital settings.

Designing tools to support advanced users in new forms of social media interaction

Interface design practices in social media systems change rapidly, routinely presenting new tools and functionalities. In order to attract a broad base of users and acceptance of system enhancements, interface designs are typically highly conventional, building on best practices in HCI. In such systems, the needs of advanced users are often secondary. To probe how the design of tools should be adjusted to the needs of advanced users, we created CrediVis, a tool for visualizing multi-dimensional user data in Wikipedia. Through a two-round study of advanced users, we find that such users value specialized and complex tools designed to fit their needs. We further observed that although they value such advanced tools they prefer conventional rather than novel interface design. Our study suggests that tool design for advanced users must be closely aligned with needs that can be co-discovered with advanced users.

Exploring the Community of Blind or Visually Impaired People on YouTube

We explore a community of blind or visually impaired (BVI) people through video blogs (vlogs) on YouTube. Many researchers have used vlogs as a means of identifying communities of video bloggers (vloggers). Nevertheless, little is still known about how BVI vloggers interact through vlogs in video-based social media. To fill the gap, we identified BVI vloggers and types of the vlogs they produced by analyzing videos on YouTube. Also, we found how BVI vloggers were connected with each other through vlogs. To our knowledge, this is the first attempt utilizing vlogs to understand the community of BVI people on YouTube.

Nursing Informatics Research Priorities for the Future: Recommendations from an International Survey.

We present one part of the results of an international survey exploring current and future nursing informatics (NI) research trends. The study was conducted by the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA-NISIG) Student Working Group. Based on findings from this cross-sectional study, we identified future NI research priorities. We used snowball sampling technique to reach respondents from academia and practice. Data were collected between August and September 2015. Altogether, 373 responses from 44 countries were analyzed. The identified top ten NI trends were big data science, standardized terminologies (clinical evaluation/implementation), education and competencies, clinical decision support, mobile health, usability, patient safety, data exchange and interoperability, patient engagement, and clinical quality measures. Acknowledging these research priorities can enhance successful future development of NI to better support clinicians and promote health internationally.

Current Trends in Nursing Informatics: Results of an International Survey.

Nursing informatics (NI) can help provide effective and safe healthcare. This study aimed to describe current research trends in NI. In the summer 2015, the IMIA-NI Students Working Group created and distributed an online international survey of the current NI trends. A total of 402 responses were submitted from 44 countries. We identified a top five NI research areas: standardized terminologies, mobile health, clinical decision support, patient safety and big data research. NI research funding was considered to be difficult to acquire by the respondents. Overall, current NI research on education, clinical practice, administration and theory is still scarce, with theory being the least common. Further research is needed to explain the impact of these trends and the needs from clinical practice.

Understanding Blind or Visually Impaired People on YouTube through Qualitative Analysis of Videos

In this paper, we analyzed videos to explore blind or visually impaired (BVI) people on YouTube. While researchers found how BVI people interact with contents and other people on social media platforms (e.g., Facebook), little is known about the experience of BVI people on video-based social media platforms (e.g., YouTube). To use videos as a mean of identifying the needs of BVI people on YouTube, we collected and analyzed a specific type of video called Visually Impaired People (VIP) Tag video. This Tag video has a set of structured questions about eye condition and experience as a BVI person. Based on the qualitative analysis of 24 VIP Tag videos created by BVI people, we found how they create videos and why they joined YouTube. In conclusion, we present how video-content analysis can be used to create an inclusive video-based social media platform.

Understanding Users’ Privacy Attitudes through Subjective and Objective Assessments: An Instagram Case Study

Although previous studies have investigated social media users’ privacy attitudes, little focus has been placed on understanding the degree of users’ concern about different types of private information or the changes in users’ privacy attitudes. This article presents novel insights on user attitudes toward 18 privacy items—identified through a review of the literature—and attitudinal changes through a comparative analysis. The authors also discuss the implications of the results that could better support users’ privacy management on social media.

Personas and Scenarios to Design Technologies for North Korean Defectors with Depression

Depression among North Korean defectors is becoming more common in South Korea. Our goal was to design technologies for North Korean defectors with depression. To identify the needs of our target population, we created personas and scenarios by incorporating known factors from previous studies. The findings from our work highlight that North Korean defectors may have special needs due to their special backgrounds. With these special requirements, we will attempt to produce a solution by designing technologies to support the defectors experiencing depression.

Designing community of practice systems: a value sensitive approach

This paper presents a process for designing an online Community of Practice (CoP) system for nurses. First, we used Value Sensitive Design by identifying the four features: benefits, harms, future trend, and pervasiveness of the CoP system to stakeholders. Next, we created two personas that represent direct stakeholders. We then incorporated the four features and personas into value scenarios. Based on the needs and barriers of potential users described in the scenarios, we created a paper prototype and evaluated its usability using three approaches: heuristic evaluation (HE), Wizard-of-Oz, and surveys. Our findings from the HE and Wizard-of-Oz methods demonstrated design flaws, as well as users’ needs and barriers in interacting with the prototype. To sum up, this paper demonstrates a design process using personas and Value Sensitive Design. We also show an evaluation process using multiple usability testing methods that could be potentially used in the early stage of development.