arXiv subjects

Hideaki Kuzuoka

Publications and source records attributed to Hideaki Kuzuoka.

7 recordsLinked to original sources

arXiv2026

Challenges in Synchronous & Remote Collaboration Around Visualization

We characterize 16 challenges faced by those investigating and developing remote and synchronous collaborative experiences around visualization. Our work reflects the perspectives and prior research efforts of an international group of 29 experts from across human-computer interaction and visualization sub-communities. The challenges are anchored around five collaborative activities that exhibit a centrality of visualization and multimodal communication. These activities include exploratory data analysis, creative ideation, visualization-rich presentations, joint decision making grounded in data, and real-time data monitoring. The challenges also reflect the changing dynamics of these activities in the face of recent advances in extended reality (XR) and artificial intelligence (AI). As an organizing scheme for future research at the intersection of visualization and computer-supported cooperative work, we align the challenges with a sequence of four sets of research and development activities: technological choices, social factors, AI assistance, and evaluation.

cs.HC↗

arXiv2026

Effects of Social Contextual Variation Using Partner Avatars on Memory Acquisition and Retention

This study investigates how partner avatar design affects learning and memory when an avatar serves as a lecturer. Based on earlier research on the environmental context dependency of memory, we hypothesize that the use of diverse partner avatars results in a slower learning rate but better memory retention than that of a constant partner avatar. Accordingly, participants were tasked with memorizing Tagalog--Japanese word pairs. On the first day of the experiment, they repeatedly learned the pairs over six sessions from a partner avatar in an immersive virtual environment. One week later, on the second day of the experiment, they underwent a recall test in a real environment. We employed a between-participants design to compare the following conditions: the varied avatar condition, in which each repetition used a different avatar, and the constant avatar condition, in which the same avatar was used throughout the experiment. Results showed that participants in the varied avatar condition recalled significantly worse during the learning trials on the first day. However, we found no significant difference between conditions in the delayed recall test on the second day. We discuss these effects in relation to the social presence of the partner avatar. This study opens up a novel approach to optimizing the effectiveness of instructor avatars in immersive virtual environments.

cs.HC↗

arXiv2026

Punchlines Unbound: Comedy Practices in Social Virtual Reality

Social VR platforms serve as an emergent venue for live performance, enabling co-presence and real-time interaction among distributed performers and audiences within shared virtual environments. Live performances, such as comedy, rely on subtle social cues between performers and audiences, which are missing in VR. However, it remains unclear how comedians utilize avatar-mediated cues in social VR. We conducted semi-structured interviews and observations with 23 virtual comedians on VRChat. Results revealed that virtual comedians transformed their limited nonverbal expressiveness into performative opportunities through intentional control and exaggeration. Additionally, a distinctive culture emerged around context-appropriate emoji reactions from audiences, while challenges such as audio latency and moderation against trolling were highlighted. Our findings advance understanding of how performers creatively adapt to expressive constraints in avatar-mediated settings. We further demonstrate how challenges in performer-audience interaction and moderation provide design insights for systems enhancing feedback visibility and sustain community norms without restricting creative expression.

cs.HC↗

arXiv2025

Understanding and Supporting Co-viewing Comedy in VR with Embodied Expressive Avatars

Co-viewing videos with family and friends remotely has become prevalent with the support of communication channels such as text messaging or real-time voice chat. However, current co-viewing platforms often lack visible embodied cues, such as body movements and facial expressions. This absence can reduce emotional engagement and the sense of co-presence when people are watching together remotely. Although virtual reality (VR) is an emerging technology that allows individuals to participate in various social activities while embodied as avatars, we still do not fully understand how this embodiment in VR affects co-viewing experiences, particularly in terms of engagement, emotional contagion, and expressive norms. In a controlled experiment involving eight triads of three participants each (N=24), we compared the participants' perceptions and reactions while watching comedy in VR using embodied expressive avatars that displayed visible laughter cues. This was contrasted with a control condition where no such embodied expressions were presented. With a mixed-method analysis, we found that embodied laughter cues shifted participants' engagement from individual immersion to socially coordinated participation. Participants reported heightened self-awareness of emotional expression, greater emotional contagion, and the development of expressive norms surrounding co-viewers' laughter. The result highlighted the tension between individual engagement and interpersonal emotional accommodation when co-viewing with embodied expressive avatars.

cs.HC↗

arXiv2025

Understanding and Supporting Peer Review Using AI-reframed Positive Summary

While peer review enhances writing and research quality, harsh feedback can frustrate and demotivate authors. Hence, it is essential to explore how critiques should be delivered to motivate authors and enable them to keep iterating their work. In this study, we explored the impact of appending an automatically generated positive summary to the peer reviews of a writing task, alongside varying levels of overall evaluations (high vs. low), on authors' feedback reception, revision outcomes, and motivation to revise. Through a 2x2 online experiment with 137 participants, we found that adding an AI-reframed positive summary to otherwise harsh feedback increased authors' critique acceptance, whereas low overall evaluations of their work led to increased revision efforts. We discuss the implications of using AI in peer feedback, focusing on how AI-driven critiques can influence critique acceptance and support research communities in fostering productive and friendly peer feedback practices.

cs.HC↗

arXiv2025

Understanding and Supporting Formal Email Exchange by Answering AI-Generated Questions

Replying to formal emails is time-consuming and cognitively demanding, as it requires crafting polite phrasing and providing an adequate response to the sender's demands. Although systems with Large Language Models (LLMs) were designed to simplify the email replying process, users still need to provide detailed prompts to obtain the expected output. Therefore, we proposed and evaluated an LLM-powered question-and-answer (QA)-based approach for users to reply to emails by answering a set of simple and short questions generated from the incoming email. We developed a prototype system, ResQ, and conducted controlled and field experiments with 12 and 8 participants. Our results demonstrated that the QA-based approach improves the efficiency of replying to emails and reduces workload while maintaining email quality, compared to a conventional prompt-based approach that requires users to craft appropriate prompts to obtain email drafts. We discuss how the QA-based approach influences the email reply process and interpersonal relationship dynamics, as well as the opportunities and challenges associated with using a QA-based approach in AI-mediated communication.

cs.HC↗

arXiv2024

Reduction of Forgetting by Contextual Variation During Encoding Using 360-Degree Video-Based Immersive Virtual Environments

Recall impairment in a different environmental context from learning is called context-dependent forgetting. Two learning methods have been proposed to prevent context-dependent forgetting: reinstatement and decontextualization. Reinstatement matches the environmental context between learning and retrieval, whereas decontextualization involves repeated learning in various environmental contexts and eliminates the context dependency of memory. Conventionally, these methods have been validated by switching between physical rooms. However, in this study, we use immersive virtual environments (IVEs) as the environmental context assisted by virtual reality (VR), which is known for its low cost and high reproducibility compared to traditional manipulation. Whereas most existing studies using VR have failed to reveal the reinstatement effect, we test its occurrence using a 360-degree video-based IVE with improved familiarity and realism instead of a computer graphics-based IVE. Furthermore, we are the first to address decontextualization using VR. Our experiment showed that repeated learning in the same constant IVE as retrieval did not significantly reduce forgetting compared to repeated learning in different constant IVEs. Conversely, repeated learning in various IVEs significantly reduced forgetting than repeated learning in constant IVEs. These findings contribute to the design of IVEs for VR-based applications, particularly in educational settings.

cs.HC↗