Account sharing is common in subscription services and is now extending to generative AI platforms, which are still primarily designed for individual use. Sharing often requires workarounds that create new tensions. This study examines how LLM subscriptions are shared and the norms that develop. We combined a survey of 245 users with interviews of 36 participants to understand both patterns and lived experiences. Our analysis identified four types of account sharing, organized along two dimensions: whether the owner uses the account and whether subscription costs are shared. Within these types, we examined how norms were formed and how their fragility, especially privacy, became evident in practice. Users, fully aware of this, subtly adjusted their behavior, which we interpret through the lens of the observer effect. We frame LLM account sharing as a social practice of appropriation and outline design implications to adapt single-user platforms to multi-user realities.

Natural language-based AI services like ChatGPT are gaining attention in writing. However, while utilizing LLMs, many users do not receive desired answers in one attempt and resort to multiple reprompts. Despite the frequent occurrence of these trial-and-error processes, research on this issue remains limited. Therefore, this study analyzes user dissatisfaction and response strategies during continuous conversations, focusing on reprompting in writing tasks using ChatGPT. Fifteen participants completed a writing task in three rounds using ChatGPT. Analysis of collected log data and in-depth interviews revealed most users were unsatisfied after a single prompting, leading to reprompting. Additionally, during continuous conversations, users experienced two dissatisfaction patterns: repeatedly facing the same dissatisfaction or encountering unexpected new dissatisfaction after resolving previous issues. In these cases, users tended to try various strategies without clear direction. Based on these findings, we discuss users' perceptions and suggest implications for future interface design.

Effective voice agent (VA) counseling necessitates the interpretation of verbal cues alongside non-verbal behaviors, with a specific focus on user gaze. We aim to understand users’ gaze behavior in VA counseling and investigate its impact on response strategies. We developed GC-Speaker to detect user gaze direction during counseling, collecting 339 utterances and 678 gaze instances from 23 participants. For analysis, we categorized user gaze behaviors into three conditions: Non-Gaze, Once-Gaze, and Full-Gaze. The analysis showed Once-Gaze utterances were longer and had higher word counts than Non-Gaze and Full-Gaze utterances. Additionally, a gaze shift was observed, with Once-Gaze notably transitioning between conditions, while Non-Gaze and Full-Gaze remained stable. Interviews further revealed that users prefer to use gaze behavior in serious conversations, such as when expecting specific answers, navigating long utterances. These findings suggest that incorporating user gaze analysis into counseling dialogues can lead to more adaptive and effective responses in VA counseling.

Since the COVID-19 pandemic, video conferencing platforms have given rise to new virtual activities, such as virtual study rooms where users utilize video to share ambient presence for study motivation. In virtual study rooms, it can be challenging for the users to determine what to reveal and what to hide on camera, as the video needs to strongly convey their presence without revealing more than necessary. In this paper, we investigate the conflicting needs of virtual study room users to reveal and hide on camera, as well as the methods they employ to cope with these needs using videos. To this end, we conducted a three-step qualitative study. The first study involved interviews to discover the key user needs that entail the conflict to reveal and hide. The second study utilized virtual study room screen analysis to identify the video features that characterize virtual study room videos. In the last study, we employed interviews to associate the video features with the key user needs. Based on these findings, we discussed the effects of studying together that could be applied to a non-physical and non-interactive co-studying environment and the need for further development of video conferencing tools to effectively share ambient presence.

A user's ownership perception of virtual objects, such as cloud files, is generally uncertain. Is this valid for streaming platforms featuring accounts designed for sharing (DS)? We observe sharing practices within DS accounts of streaming platforms and identify their ownership characteristics and unexpected complications through two mixed-method studies. Casual and Cost-splitting are the two sharing practices identified. The owner is the sole payer for the account in the former, whereas profile holders split the cost in the latter. We distinguish two types of ownership in each practice—Primary and Dual. In Primary ownership, the account owner has the power to allow others to use the account; in Dual ownership, Primary ownership appears in conjunction with joint ownership, notably displaying asymmetric ownership perceptions among users. Conflicts arise when the sharing agreements collapse. Therefore, we propose design recommendations that bridge ownership differences based on sharing practices of DS accounts.

As smartphones can handle work and leisure activities simultaneously, cyberslacking and the collapse of work-life balance are causing social problems. Hence, in this study we analyzed users’ smartphone usage behavior and the transition pattern between work and non-work behaviors using log data collected automatically from an actual site. The collected log data were divided into four types of sessions according to work-related characteristics. No significant difference was found in frequency, usage time, or app type between work conditions. Additionally, the pattern of consecutively switching between work and non-work conditions more than four times occurred the most. This results in work and non-work behaviors on smartphones being mixed, with chemical convergence beyond the physical level. Thus, we assert that a new method of smartphone management that will selectively block micro-activity within each app is needed beyond self-discipline or existing blocking approaches in the workplace.

In the Korean entertainment industry, there exists `photaku' -a particular group of fans who take photos and videos of their favorite celebrities and distribute them online. To find out structures of their activities, we used a multi-method approach using in-depth interviews, offline observation, and social media analysis. Our findings demonstrate that photaku engage in four types of unique activities: one main activity to distribute photos and videos and three types of secondary activities: strengthening their competitiveness, supporting celebrities and monetization.

Due to the prevalence of personal health tracking, cases of self-logged data being utilized in the clinic are gradually increasing. However, obstacles to clinicians' ability to further adopt such data-driven medical consultations in the existing workflow remain, such as lack of time and poor interoperability. In this paper, we conducted a workshop to design a clinician interface supporting the integration of data-driven consultation into the existing workflow and investigate the role of the interface in situ. After implementing the clinician interface designed based on the workshop results, we observed 32 cases of actual use within the clinical context. We found that our interface, DataMD, helped the clinician construct a new workflow, enhanced the clinician's counseling skills, and facilitated more in-depth conversation. This paper contributes to empirically identifying the role of a clinician interface through a user-centered design approach.

By enabling people to track their lifestyles, including activity level, sleeping, and diet, technology helps clinicians to treat patients suffering from "lifestyle diseases." However, despite its importance compared to other lifestyle factors, it is not easy to record food intake consistently. Although researchers have attempted to solve this problem, most have not considered its applicability in the clinical context. In this paper, we aim to (1) understand food-journaling practices and (2) explore the applicability of lifestyle data in the clinical context. By observing 20 patients who recorded data including food logs, steps, and sleeping time, we found that patients recorded their food logs diligently, as they were conscious of clinicians. Clinicians were surprised by the high adherence rate of journaling and tried to overlap food data with other data, such as steps, sleeping time, etc. This paper contributes by providing qualitative insights for designing applicable strategies utilizing lifestyle data in the clinical context.