Decentralized Web3 Non-Fungible Token Community for Societal Prosperity? A Social Capital Perspective In the rapidly evolving Web3 world, non-fungible token (NFT) communities are reshaping the formation, distribution, and activation of social capital in ways distinct from traditional models. However, despite their growing impact on societal prosperity, a comprehensive understanding of social capital dynamics within Web3 NFT communities remains limited. This study explores the Mfers community, a key example within Web3 NFT ecosystems. By analyzing social media and blockchain data and using a Delphi method-based human-large language model (LLM) collaboration, we uncovered unique social capital patterns across six dimensions. Our findings highlight a compelling blend of decentralization, inclusion, trust, and empowerment but also raise critical questions about wealth inequality, content quality, and ethical challenges. Based on the findings, we discussed the uniqueness of social capital in Web3 NFT communities, the tension between technical and power decentralization, and the multidimensional nature of societal prosperity. We also suggested directions for future research on decentralized online communities in the CSCW field. This study provides a systematic perspective on social capital in Web3 NFT communities and introduces an innovative human-LLM collaborative analysis, offering insights into the design and governance of benign decentralized online communities.
Getting Things Done With AI
CSCW 2025 "If I were in Space": Understanding and Adapting to Social Isolation through Designing Collaborative Storytelling Social isolation can lead to pervasive health issues like anxiety and loneliness. Previous work focused on physical interventions like exercise and teleconferencing, but overlooked the narrative potential of adaptive strategies. To address this, we designed a collaborative online storytelling experience in social VR, enabling participants in isolation to design an imaginary space journey as a metaphor for quarantine, in order to learn about their isolation adaptation strategies in the process. Eighteen individuals participated during real quarantine undertaken a virtual role-play experience, designing their own spaceship rooms and engaging in collaborative activities that revealed creative adaptative strategies. Qualitative analyses of participant designs, transcripts, and interactions revealed how they coped with isolation, and how the engagement unexpectedly influenced their adaptation process. This study shows how designing playful narrative experiences, rather than solution-driven approaches, can serve as probes to surface how people navigate social isolation.
Social & Collaborative VR Identity & Avatars in XR STEM Education & Science Communication
DIS 2025 ``I am not the primary focus" - Understanding the Perspectives of Bystanders in Photos Shared Online When taking photos in a crowd, unintended individuals, such as bystanders, are often captured alongside the main subject(s). In an effort to protect bystanders' privacy, existing methods have been developed to automatically detect bystanders. However, inconsistent definitions of who qualifies as a bystander limit their effectiveness. To better understand bystanders' perceptions, we conducted an online survey with 486 participants, analyzing their responses to 864 image-based scenarios and their comfort with sharing these images online. Our results revealed no significant correlation between comfort with public photo sharing and bystander status. We identified limitations in current bystander detection methodologies, as they often fail to recognize bystanders who are not clearly in the background, hence missing individuals with privacy concerns. Moreover, comfort with public sharing varied significantly depending on the image context. Our findings highlight the importance of considering the context of captured images to address privacy concerns in image sharing.
YN
Yuqi Niu et al. Shanghai Jiao Tong University; The University of Edinburgh, School of Informatics
Privacy by Design & User Control Privacy Perception & Decision-Making Misinformation & Fact-Checking
CHI 2025 Crossmodal Interactions in Human-Robot Communication: Exploring the Influences of Scent and Voice Congruence on User Perceptions of Social Robots Olfactory stimuli have demonstrated the potential to evoke emotional depth and enhance user experiences in HCI. Yet, their role in shaping perceptions of social robots remains largely untapped. This study investigates how olfactory (scent) and auditory (voice) stimuli influence user perceptions of social robots. Using a 2x2 between-subjects design, participants interacted with a social robot under conditions with pleasant/unpleasant scents and friendly/unfriendly voices. The study measured perceived trust, friendliness, competence, and engagement. Our findings show that pleasant scents can enhance the perceptions of friendliness and engagement, while friendly voices can improve trust, friendliness, and engagement. The congruent combination of scents and voices affects friendliness and engagement but does not influence trust and competence. This study contributes to the growing work on multi-sensory Human-Robot Interaction (HRI) design, offering implications for creating more socially interactive robots.
FC
Fangyuan Chang et al. Shanghai Jiao Tong University, School of Design
Mid-Air Haptics (Ultrasonic) Social Robot Interaction
CHI 2025 Ad Recommended
Learn AI Coding at CodeNow open_in_new M^2Silent: Enabling Multi-user Silent Speech Interactions via Multi-directional Speakers in Shared Spaces We introduce M^2Silent, which enables multi-user silent speech interactions in shared spaces using multi-directional speakers. Ensuring privacy during interactions with voice-controlled systems presents significant challenges, particularly in environments with multiple individuals, such as libraries, offices, or vehicles. M^2Silent addresses this by allowing users to communicate silently, without producing audible speech, using acoustic sensing integrated into directional speakers. We leverage FMCW signals as audio carriers, simultaneously playing audio and sensing the user's silent speech. To handle the challenge of multiple users interacting simultaneously, we propose time-shifted FMCW signals and blind source separation algorithms, which help isolate and accurately recognize the speech features of each user. We also present a deep-learning model for real-time silent speech recognition. M^2Silent achieves Word Error Rate (WER) of 6.5% and Sequence Error Rate (SER) of 12.8% in multi-user silent speech recognition while maintaining high audio quality, offering a novel solution for privacy-preserving, multi-user silent interactions in shared spaces.
JZ
Juntao Zhou et al. Shanghai Jiao Tong University, Department of Computer Science and Engineering
Eye Tracking & Gaze Interaction Voice User Interface (VUI) Design Privacy by Design & User Control
CHI 2025 How the Algorithmic Transparency of Search Engines Influences Health Anxiety: The Mediating Effects of Trust in Online Health Information Search Advancements in artificial intelligence-powered search engines have enhanced the efficiency of online health information searches by generating direct answers to queries using top-ranked featured snippets (FS). However, such functionalities may contribute to health anxiety, particularly when the displayed results are distressing. This study investigated the effect of algorithmic transparency (AT) explanations (absence vs. presence) on mitigating FS-triggered health anxiety. The results of an online experiment (N = 206) yielded two key findings: First, participants exposed to AT explanations detailing the selection process of FS experienced reduced trust in the search engine and distressing results, which subsequently alleviated health anxiety. Second, the moderating effect of pre-existing cyberchondria on the relationship between AT explanations and trust was observed, but only within a limited threshold. Overall, the findings empirically validate AT explanations as an effective approach to mitigate FS-induced health anxiety. Theoretical and practical implications are discussed.
YW
Yuheng Wu et al. Shanghai Jiao Tong University, School of Media and Communication; City University of Hong Kong, Department of Media and Communication
Explainable AI (XAI) Algorithmic Transparency & Auditability Privacy Perception & Decision-Making
CHI 2025 Collaborative Health-Tracking Technologies for Children and Parents: A Review of Current Studies and Directions for Future Research Collaborative health-tracking technologies for children and parents have gained significant attention in recent years in HCI. This review examines the current state of these technologies by analyzing 29 studies screened from 15,973 search results across three databases. Our findings revealed three primary goals in these technologies: promoting family health, improving children’s health through child-parent co-tracking, and fostering children’s independence in self-tracking. For each goal, we examined child-parent roles, data types collected, and features that facilitate or hinder collaboration. Our findings highlight key directions for future research, including designing adaptable technologies to reflect evolving child-parent roles, exploring different technologies and tracking topics that impact child-parent dynamics, involving children in the system design stage to enhance collaborative features, and studying diverse populations with varied family characteristics. These insights aim to guide the creation of more effective and inclusive collaborative health-tracking technologies for children and parents.
YC
Yoon Jeong Cha et al. University of Michigan, School of Information
Mental Health Apps & Online Support Communities Fitness Tracking & Physical Activity Monitoring Sleep & Stress Monitoring
CHI 2025 emoji_events EchoBreath: Continuous Respiratory Behavior Recognition in the Wild via Acoustic Sensing on Smart Glasses Monitoring the occurrence count of abnormal respiratory symptoms helps provide critical support for respiratory health. While this is necessary, there is still a lack of an unobtrusive and reliable way that can be effectively used in real-world settings. In this paper, we present EchoBreath, a passive and active acoustic combined sensing system for abnormal respiratory symptoms monitoring. EchoBreath novelly uses the speaker and microphone under the frame of the glasses to emit ultrasonic waves and capture both passive sounds and echo profiles, which can effectively distinguish between subject-aware behaviors and background noise. Furthermore, A lightweight neural network with the 'Null' class and open-set filtering mechanisms substantially improves real-world applicability by eliminating unrelated activity. Our experiments, involving 25 participants, demonstrate that EchoBreath can recognize 6 typical respiratory symptoms in a laboratory setting with an accuracy of 93.1%. Additionally, an in-the-semi-wild study with 10 participants further validates that EchoBreath can continuously monitor respiratory abnormalities under real-world conditions. We believe that EchoBreath can serve as an unobtrusive and reliable way to monitor abnormal respiratory symptoms.
KG
Kaiyi Guo et al. shanghai jiao tong university, school of software
Biosensors & Physiological Monitoring Context-Aware Computing
CHI 2025 emoji_events Developing a Social Support Framework: Understanding the Reciprocity in Human-Chatbot Relationship Chatbots are increasingly used to provide social support for individuals with mental health challenges. However, a systematic analysis of the types and directionality of support within chatbot use remains lacking. This study establishes a framework for understanding reciprocal social support exchanges in human-chatbot relationships, focusing on the popular chatbot, Replika. By analyzing 496 posts and 20,494 comments from the largest Replika community on Reddit, we identified 27 support subcategories, organized into five main types (functional, informational, emotional, esteem, and network) and two directions (chatbot-receiving and chatbot-giving). Our findings reveal significant yet controversial issues, such as subscription services and chatbot-displayed affection. Notably, "user teaching chatbot" emerged as a core aspect of the human-chatbot relationship, covering how users actively guide and refine the chatbot’s learning or algorithm. This study constructs a novel social support framework for chatbot use, highlighting the potential for reciprocal support exchanges between users and chatbots.
SP
Shuyi Pan et al. Shanghai Jiao Tong University; Utrecht University
Conversational Chatbots Agent Personality & Anthropomorphism Mental Health Apps & Online Support Communities
CHI 2025 VISAR: Projecting Virtual Sound Spots for Acoustic Augmented Reality Using Air Nonlinearity Zhou 等人提出 VISAR 系统，利用空气非线性特性在声学增强现实中投射虚拟声点，为用户提供沉浸式音频体验。
Voice User Interface (VUI) Design AR Navigation & Context Awareness
UbiComp 2024 SF-Adapter: Computational-Efficient Source-Free Domain Adaptation for Human Activity Recognition Kang 等人提出 SF-Adapter 框架，实现计算高效的无源域自适应人体活动识别，在不访问源域数据的情况下降低领域偏移的影响。
Human Pose & Activity Recognition
UbiComp 2024 SkipWriter: LLM-Powered Abbreviated Writing on Tablets Large Language Models (LLMs) may offer transformative opportunities for text input, especially for physically demanding modalities like handwriting. We studied a form of abbreviated handwriting by designing, developing, and evaluating a prototype, named SkipWriter, that converts handwritten strokes of a variable-length prefix-based abbreviation (e.g. "ho a y" as handwritten strokes) into the intended full phrase (e.g., "how are you" in the digital format) based on the preceding context. SkipWriter consists of an in-production handwriting recognizer and an LLM fine-tuned on this task. With flexible pen input, SkipWriter allows the user to add and revise prefix strokes when predictions do not match the user's intent. An user evaluation demonstrated a 60% reduction in motor movements with an average speed of 25.78 WPM. We also showed that this reduction is close to the ceiling of our model in an offline simulation.
Human-LLM Collaboration Motor Impairment Assistive Input Technologies Knowledge Worker Tools & Workflows
UIST 2024 HandPad: Make Your Hand an On-the-go Writing Pad via Human Capacitance The convenient text input system is a pain point for devices such as AR glasses, and it is difficult for existing solutions to balance portability and efficiency. This paper introduces HandPad, the system that turns the hand into an on-the-go touchscreen, which realizes interaction on the hand via human capacitance. HandPad achieves keystroke and handwriting inputs for letters, numbers, and Chinese characters, reducing the dependency on capacitive or pressure sensor arrays. Specifically, the system verifies the feasibility of touch point localization on the hand using the human capacitance model and proposes a handwriting recognition system based on Bi-LSTM and ResNet. The transfer learning-based system only needs a small amount of training data to build a handwriting recognition model for the target user. Experiments in real environments verify the feasibility of HandPad for keystroke (accuracy of 100%) and handwriting recognition for letters (accuracy of 99.1%), numbers (accuracy of 97.6%) and Chinese characters (accuracy of 97.9%).
Hand Gesture Recognition Foot & Wrist Interaction
UIST 2024 Rehab-Diary: Enhancing Recovery Identity with an Online Support Group for Middle Aged and Older Ovarian Cancer Patients Ovarian cancer presents significant well-being challenges for middle-aged and older women. Recent research underscores the vital role of recovery identity in predicting wellbeing. However, a research gap exists regarding the influence of online support groups (OSPs) on identity synthesis for middle-aged and older cancer patients. This study introduces "Rehab-Diary," a mobile age-friendly OSP grounded in The Social Identity Model of Identity Change, aimed at helping ovarian cancer patients foster recovery identity. A four-week randomized controlled trial involving 68 participants assessed the OSP's impact. The interface was tailored for ease of use by older individuals. The findings demonstrate the feasibility of utilizing Rehab-Diary among older individuals. The intervention effectively enhanced recovery identity. This study offers evidence-based insights for developing future age-friendly online support interventions, ultimately enhancing ovarian cancer patients' quality of care.
Aging-Friendly Technology Design Mental Health Apps & Online Support Communities
MobileHCI 2024 Starrypia: An AR Gamified Music Adjuvant Treatment Application for Children with Autism Based on Combined Therapy In this paper, we present Starrypia, a lightweight gamified music adjuvant treatment application to improve the symptoms of mild autistic children, eliminating the geographical and time constraints faced by traditional treatment. Adopting ABA (Applied Behavior Analysis) behavioral theory as the principle, Starrypia follows the stimulus-response-reinforcement-pause process and incorporates music therapy and sensory integration. Based on AR, Starrypia provides multi-sensory intervention through music generated by BiLSTM deep model, 3D visual scenes, touch interaction to keep children focused and calm. We conducted a controlled experiment on 20 children to test Starrypia’s effectiveness and attraction. Children’s pre-test and post-test scores on two autism rating scales and performance during the test were applied to measure their abilities and engagement. Experimental results indicated that children showed great interest in Starrypia and presented evident symptom remission and advance in overall abilities after 4 weeks of use. In conclusion, Starrypia is practicable in both therapeutic effect and user experience, and conspicuously instrumental in promoting sensory ability.
AR Navigation & Context Awareness Serious & Functional Games STEM Education & Science Communication Special Education Technology
UIST 2023 4Doodle: 4D Printing Artifacts without 3D Printers 4D printing encodes transformability over time, which empowers users to create artifacts by on-demand deformation. The creative process of 4D printing shape-changing artifacts can be challenging because of its discontinuous fabrication steps, such as digital designing, specific path planning, automatic printing and manual triggering. We hypothesize that switching from typical 4D printing reliant on 3D printers to a more “handcrafted” method can allow users to understand and continuously reflect upon the artifact and its transformability. Towards this vision, we introduce 4Doodle, a hybrid craft approach that integrates unique deformation controllability and five techniques for freehand 4D printing, using a 3D pen. To tackle the shape-changing challenges of uncertain hands-on fabrication, we develop a mixed reality system to help novices master the manual skills of 4D printing. We also demonstrate a series of 4D printed artifacts with fully human intervention. Finally, our user study shows that 4Doodle lowers the skill-acquisition barrier associated with handcrafting 4D printed artifacts, and it has great potential for creative production and spatial ability.
YT
Ye Tao et al. Zhejiang University City College
Shape-Changing Interfaces & Soft Robotic Materials Shape-Changing Materials & 4D Printing Digital Art Installations & Interactive Performance
CHI 2023 Emotional Labor in Everyday Resilience: Class-Based Experiences of Navigating Unemployment Amid the COVID-19 Pandemic in the U.S. During the coronavirus disease 2019 (COVID-19) global health crisis, institutions, policymakers, and academics alike have called for practicing resilience to overcome its ongoing disruptions. This paper contributes a comparative study of the job search experiences of working-class and upper-middle-class job seekers, particularly in relation to their resilience practices during the pandemic. We draw from interviews with 12 working-class and 11 upper-middle-class job seekers in the U.S. We unpack challenges resulting from both the pandemic and unemployment and job seekers' novel practices of navigating these challenges in their everyday disrupted life, highlighting the similarities and differences across classes. Job seekers' ongoing negotiation with their resources, situations, and surroundings gives practical meanings to building everyday resilience, which we conceptualize as an ongoing process of becoming resilient. We found that job seekers across classes experienced similar challenges. However, working-class job seekers took on additional emotional labor in their everyday resilience due to their limited experience in the digital job search space, competition with higher-degree holding job seekers applying for the same jobs, limited social support networks, and at times, isolation. By foregrounding the uneven distribution of emotional labor in realizing the promise of resilience along class lines, this work cautions against the romanticization of resilience and calls for a more critical understanding of resilience in CSCW.
Pandemic Life; Pandemic Life
CSCW 2022 To Use or Abuse: Opportunities and Difficulties in the Use of Multi-channel Support to Reduce Technology Abuse by Adolescents Technology abuse among adolescents refers to the problematic use of technology devices, and the negative impact it can have on lifestyle and one’s physical and mental health. This paper reports on in-depth interviews with 15 dyads of adolescent patients, their parents, and four experts with the objective of unraveling the issue of technology abuse. We conducted qualitative analysis aimed at unpacking the contextual factors affecting technology abuse, and differences between adolescents and their parents pertaining to this issue. Our discussions led us to formulate solutions to technology abuse: (1) motivating adolescents by sending timely reminders and providing interactive micro-incentives; (2) promoting communication between adolescents and their parents by sharing usage data related to device usage; and (3) incorporating social supports to complement parental support, while fulfilling the adolescent’s social needs. This paper provides valuable insights into the design of technological solutions aimed at mediating technology abuse.
Health and Consultation Practices, Addictive Behaviors, and Social Re-entry; Health and Consultation Practices, Addictive Behaviors, and Social Re-entry
CSCW 2022 Phrase-Gesture Typing on Smartphones We study phrase-gesture typing, a gesture typing method that allows users to type short phrases by swiping through all the letters of the words in a phrase using a single, continuous gesture. Unlike word-gesture typing, where text needs to be entered word by word, phrase-gesture typing enters text phrase by phrase. To demonstrate the usability of phrase-gesture typing, we implemented a prototype called PhraseSwipe. Our system is composed of a frontend interface designed specifically for typing through phrases and a backend phrase-level gesture decoder developed based on a transformer-based neural language model. Our decoder was trained using five million phrases of varying lengths of up to five words, chosen randomly from the Yelp Review Dataset. Through a user study with 12 participants, we demonstrate that participants could type using PhraseSwipe at an average speed of 34.5 WPM with a Word Error Rate of 1.1%.
Voice User Interface (VUI) Design Generative AI (Text, Image, Music, Video)
UIST 2022 One Week in the Future: Previs Design Futuring for HCI Research We explore the use of cinematic "pre-visualization" (previs) techniques as a rapid ideation and design futuring method for human computer interaction (HCI) research. Previs approaches, which are widely used in animation and film production, use digital design tools to create medium-fidelity videos that capture richer interaction, motion, and context than sketches or static illustrations. When used as a design futuring method, previs can facilitate rapid, iterative discussions that reveal tensions, challenges, and opportunities for new research. We performed eight one-week design futuring sprints, in which individual HCI researchers collaborated with a lead designer to produce concept sketches, storyboards, and videos that examined future applications of their research. From these experiences, we identify recurring themes and challenges and present a One Week Futuring Workbook that other researchers can use to guide their own futuring sprints. We also highlight how variations of our approach could support other speculative design practices.
AI
Alexander Ivanov et al. University of Calgary
Design Fiction Interactive Narrative & Immersive Storytelling
CHI 2022