Communication and Collaboration

会議の名前
CHI 2024
Understanding Entrainment in Human Groups: Optimising Human-Robot Collaboration from Lessons Learned during Human-Human Collaboration
要旨

Successful entrainment during collaboration positively affects trust, willingness to collaborate, and likeability towards collaborators. In this paper, we present a mixed-method study to investigate characteristics of successful entrainment leading to pair and group-based synchronisation. Drawing inspiration from industrial settings, we designed a fast-paced, short-cycle repetitive task. Using motion tracking, we investigated entrainment in both dyadic and triadic task completion. Furthermore, we utilise audio-video recordings and semi-structured interviews to contextualise participants' experiences. This paper contributes to the Human-Computer/Robot Interaction (HCI/HRI) literature using a human-centred approach to identify entrainment characteristics during pair- and group-based collaboration. We present five characteristics related to successful entrainment. These are related to the occurrence of entrainment, leader-follower patterns, interpersonal communication, the importance of the point-of-assembly, and the value of acoustic feedback. Finally, based on our findings, we present three design considerations for future research and design on collaboration with robots.

著者
Eike Schneiders
University of Nottingham, Nottingham, United Kingdom
Christopher K. Fourie
Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
Stanley Celestin
Cornell University, Ithaca, New York, United States
Julie Shah
MIT, Cambridge, Massachusetts, United States
Malte F. Jung
Cornell University, Ithaca, New York, United States
論文URL

https://doi.org/10.1145/3613904.3642427

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Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Spotify Blend Experiences between Two Users
要旨

Designing user experiences for group recommendation systems (GRS) is challenging, requiring a nuanced understanding of the influence of social interactions between users. Using Spotify Blend as a real-world case of music GRS, we conducted empirical studies to investigate intricate social interactions among South Korean users in GRS. Through a preliminary survey about Blend experiences in general, we narrowed the focus for the main study to relationships between two users who are acquainted or close. Building on this, we conducted a 21-day diary study and interviews with 30 participants (15 pairs) to probe more in-depth interpersonal dynamics within Blend. Our findings reveal that users engaged in implicit social interactions, including tacit understanding of their companions and indirect communication. We conclude by discussing the newly discovered value of GRS as a social catalyst, along with design attributes and challenges for the social experiences it mediates.

著者
Daehyun Kwak
KAIST, Daejeon, Korea, Republic of
Soobin Park
KAIST, Daejeon, Korea, Republic of
Inha Cha
Georgia Institute of Technology, Atlanta, Georgia, United States
Hankyung Kim
KAIST, Daejeon, Korea, Republic of
Youn-kyung Lim
KAIST, Daejeon, Korea, Republic of
論文URL

https://doi.org/10.1145/3613904.3642544

動画
Mitigating Barriers to Public Social Interaction with Meronymous Communication
要旨

In communities with social hierarchies, fear of judgment can discourage communication. While anonymity may alleviate some social pressure, fully anonymous spaces enable toxic behavior and hide the social context that motivates people to participate and helps them tailor their communication. We explore a design space of meronymous communication, where people can reveal carefully chosen aspects of their identity and also leverage trusted endorsers to gain credibility. We implemented these ideas in a system for scholars to meronymously seek and receive paper recommendations on Twitter and Mastodon. A formative study with 20 scholars confirmed that scholars see benefits to participating but are deterred due to social anxiety. From a month-long public deployment, we found that with meronymity, junior scholars could comfortably ask "newbie" questions and get responses from senior scholars who they normally found intimidating. Responses were also tailored to the aspects about themselves that junior scholars chose to reveal.

受賞
Best Paper
著者
Nouran Soliman
Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
Hyeonsu B. Kang
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Matt Latzke
Allen Institute for AI, Seattle, Washington, United States
Jonathan Bragg
Allen Institute for Artificial Intelligence, Seattle, Washington, United States
Joseph Chee Chang
Allen Institute for AI, Seattle, Washington, United States
Amy X.. Zhang
University of Washington, Seattle, Washington, United States
David R. Karger
MIT, Cambridge, Massachusetts, United States
論文URL

https://doi.org/10.1145/3613904.3642241

動画
Examining Voice Community Use
要旨

Visual online communities can present accessibility challenges to older adults or people with vision and motor disabilities. Motivated by this challenge, accessibility and HCI researchers have called for voice-based communities to support aging and disability. This paper extends prior work on voice community design and short-term use by providing empirical data on how people interact with voice communities over time and intentional instances of non-use. We conducted a one-year study with 43 blind and low vision older adults, of whom 21 used a voice-based community. We use vignettes to unpack five different voice community member roles - the obligatory poster, routine poster, cross-platform lurker, busy socialite, and visual expertise seeker - and discuss community interactions over time. Findings show how participation varied based on engagement in other communities and ways that participants sought interaction. We discuss (1) how to design voice communities for member roles and (2) the implications of synchronous and asynchronous voice community interaction in voice-only communities.

著者
Robin N.. Brewer
University of Michigan, Ann Arbor, Michigan, United States
Sam Addison. Ankenbauer
University of Michigan, Ann Arbor, Michigan, United States
Manahil Hashmi
University of Michigan, Ann Arbor, Michigan, United States
Pooja Upadhyay
University of Michigan, Ann Arbor, Michigan, United States
動画
Engaged and Affective Virtual Agents: Their Impact on Social Presence, Trustworthiness, and Decision-Making in the Group Discussion
要旨

This study investigates how different virtual agent (VA) behaviors influence subjects' perceptions and group decision-making. Participants carried out experimental group discussions with a VA exhibiting varying levels of engagement and affective behavior. Engagement refers to the VA's focus on the group task, whereas affective behavior reflects the VA's emotional state. The findings revealed that VA's engagements effectively captured participants' attention even in the group setting and enhanced group synergy, thereby facilitating more in-depth discussion and producing better consensus. On the other hand, VA's affective behavior negatively affected the perceived social presence and trustworthiness. Consequently, in the context of group discussion, participants preferred the engaged and non-affective VA to the non-engaged and affective VA. The study provides valuable insights for improving the VA's behavioral design as a team member for collaborative tasks.

著者
Hanseob Kim
Korea University, Seoul, Seoul, Korea, Republic of
Bin Han
Korea Institute of Science and Technology (KIST), Seoul, Korea, Republic of
Jieun Kim
Korea Institute of Science and Technology, Seoul, Korea, Republic of
MUHAMMAD FIRDAUS SYAWALUDIN. LUBIS
University of Indonesia, Depok, West Java, Indonesia
Gerard Jounghyun. Kim
Korea University, Seoul, NA, Korea, Republic of
Jae-In Hwang
Korea Institute of Science and Technology, Seoul, Seoul, Korea, Republic of
論文URL

https://doi.org/10.1145/3613904.3642917

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