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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Zhang-Kennedy, Leah Valiquette, Michaela Chen, An Bella Hadan, Hilda Suh, Sangho Stratford School of Interaction Design and Business University of Waterloo Waterloo ON Canada Human-Computer Interaction Carleton University Ottawa ON Canada Cheriton School of Computer Science University of Waterloo Waterloo ON Canada Department of Computer Science University of Toronto Toronto ON Canada

ISBN: (纸本)9798400713941

This study examines how anecdotal stories from friends, peers, and online sources influence non-experts' perceptions and behaviors toward smart home IoT devices. We surveyed 263 participants, collecting narratives that either positively or negatively influenced their perception of IoT devices, which they retold in text and comic formats to encourage deeper reflection. Thematic analysis of the narratives, combined with quantitative survey data, reveals that stories significantly impact trust and willingness to use and adopt IoT devices. Negative stories, particularly those concerning security, privacy, and device unreliability, reduced trust and usage, while positive stories about home safety through monitoring and improved quality of life increased interest in IoT devices. Perceptions of different IoT devices varied based on the themes associated with the stories. The findings highlight the powerful role of storytelling in driving consumer acceptance of technology. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Folk Models Internet of Things Mental Models Privacy and Security Smart Home Stories Technology Acceptance

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SimLex-999 for Dutch 30

SimLex-999 for Dutch

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Brans, Lizzy Bloem, Jelke Human Computer Interaction Utrecht University Netherlands Institute for Logic Language and Computation University of Amsterdam Netherlands Data Science Centre University of Amsterdam Netherlands

ISBN: (纸本)9782493814104

Word embeddings revolutionised natural language processing by effectively representing words as dense vectors. Although many datasets exist to evaluate English embeddings, few cater to Dutch. We developed a Dutch variant of the SimLex-999 word similarity dataset by gathering similarity judgements from 235 native Dutch speakers. Subsequently, we evaluated two popular Dutch language models, Bertje and RobBERT, finding that Bertje showed superior alignment with human semantic similarity judgments compared to RobBERT. This study provides the first intrinsic Dutch word embedding evaluation dataset, which enables accurate assessment of these embeddings and fosters the development of effective Dutch language models. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Embeddings

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Chameleon: Unobtrusive Substitution of Real-World Obstacles in VR with Risk-Level-Aware Adaptation

Chameleon: Unobtrusive Substitution of Real-World Obstacles ...

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2025 CHI Conference on human Factors in Computing Systems, CHI EA 2025

作者： Yu, Yichen Jin, Qiao Department of Computer Science University of Rochester Rochester NY United States Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9798400713958

In VR environments, free movement in real space enhances immersion but increases the risk of collisions with real-world obstacles. Prior solutions investigated using substitute obstacles with context-related digital objects in VR but often treat all obstacles uniformly without considering their varying levels of risk. This oversight might result in reduced awareness for high-risk obstacles and a missed opportunity to utilize low-risk objects to enhance haptic feedback and interactivity in VR. In this study, we propose Chameleon, a system that classifies real-world obstacles by their varying risk levels and substitutes them with context-related virtual objects in VR. The substitutions are designed to align with the obstacles’ real-world risk levels to ensure both safety and immersion. A preliminary heuristic evaluation assessed the usability of using visual textures to implicitly represent obstacle risk levels. © 2025 Copyright held by the owner/author(s).

关键词： Cross-reality System Obstacle Avoidance Safety Virtual Reality

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Korean Language NLP Model Based Emotional Analysis of LGBTQ Social Media Communities 17

Korean Language NLP Model Based Emotional Analysis of LGBTQ ...

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17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023

作者： Chi, Younghyun Kim, Jang Hyun Sun, Seungjong College of Computing and Informatics Sungkyunkwan University Department of Computer Science Suwon Korea Republic of Intelligence Interaction Sungkyunkwan University Department of Interaction Science Department of Human-Artificial Seoul Korea Republic of

ISBN: (纸本)9781665453486

Sexual minorities are increasingly gaining social visibility and legal rights guarantees at the constitutional level across much of the world, from South America, the United States, and Europe to Japan, Taiwan, and Thailand. At the same time, the COVID-19 pandemic has brought on significant mental health challenges for the public due to accompanying social and economic impact and measures, most of them adverse. Given pre-existing studies highlighting the minority demographic's vulnerability to depression and other mental health symptoms, and the increasing availability of accessible NLP tools, datasets, and models, this paper uses an emotional classification model to analyze emotional trends in queer communities on social media. Using KoBERT with a pre-labelled dataset containing some forty thousand scraped social media posts labelled with emotions, patterns of emotional expression on Twitter in the queer community is revealed. Resulting data provided a validation of the viability of this method of analyzing trends in negative and positive emotional expression as well as the impact COVID-19 had on online queer communities in early 2020 but revealed limitations. © 2023 IEEE.

关键词： Natural language processing systems

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Investigating Composite Relation with a Data-Physicalized Thing through the Deployment of the WavData Lamp 25

Investigating Composite Relation with a Data-Physicalized Th...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Zhong, Ce Li, Xiang Wang, Xizi Sun, Junwei Zhao, Jian Cheriton School of Computer Science University of Waterloo Waterloo ON Canada Huawei Human Machine Interaction Lab Markham ON Canada

ISBN: (纸本)9798400713941

This paper reports on a field study of the WavData Lamp: an interactive lamp that can physically visualize people's music listening data by changing light colors and outstretching its form enclosure. We deployed five WavData Lamps to five participants' homes for two months to investigate their composite relation with a data-physicalized thing. Findings reveal that their music-listening norms were determined by the instantiated materiality of the Lamp in the early days. With a tilted form enclosure, the WavData Lamp successfully engendered rich actions and meanings of the cohabiting participants and their family members. In the end, the participants described their experiences of entangling with and living with the Lamp as a form of collaboration. Reflecting on these empirical insights explicitly extends the intrinsic meaning of the composite relation and offers rich implications to promote further HCI explorations and practices. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Artificial intelligence Composite relation Data physicalization Research through design Technological things

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The fNIRS-based Emotion Recognition by Spatial Transformer and WGAN Data Augmentation Towards Developing A Novel Affective BCI

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IEEE Transactions on Affective Computing 2024年第2期16卷 875-890页

作者： Si, Xiaopeng Huang, He Yu, Jiayue Ming, Dong Tianjin University Academy of Medical Engineering and Translational Medicine State Key Laboratory of Advanced Medical Materials and Devices Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin Key Laboratory of Brain Science and Neural Engineering Institute of Applied Psychology Tianjin300072 China Tianjin University Academy of Medical Engineering and Translational Medicine State Key Laboratory of Advanced Medical Materials and Devices Haihe Laboratory of Brain-computer Interaction and Human-machine Integration Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin300072 China

The affective brain-computer interface (aBCI) facilitates the objective identification or regulation of human emotions. Current aBCI mainly relies on electroencephalography (EEG). However, research shows that emotions involve a large-scale distributed brain network. Compared to electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS) offers a higher spatial resolution. It holds greater potential in capturing emotional spatial information, which may foster the development of new affective Brain-computer Interfaces (aBCI). We proposed a novel self-attention-based deep-learning transformer language model for fNIRS cross-subject emotion recognition, which could automatically learn the emotion's spatial attention weight information with strong interpretability. Besides, we performed data augmentation by introducing the wasserstein generative adversarial networks (WGAN). Results showed: (1) We achieved 84% three-category cross-subject emotion decoding accuracy. The spatial transformer module and WGAN improved the accuracy by 12.8% and 4.3%, respectively. (2) Compared with cutting-edge fNIRS research, we led by 10% in three-category decoding accuracy. (3) Compared with cutting-edge EEG research, we lead by 28% in arousal decoding accuracy, 10% in valence decoding accuracy, and 2% in three-category decoding accuracy. (4) Besides, our approach holds the potential to uncover the brain's spatial encoding mechanism of human emotion processing, providing a new direction for building interpretable artificial intelligence models. © 2010-2012 IEEE.

关键词： Near infrared spectroscopy

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Virtual Displays for Knowledge Work: Extending or Replacing Physical Monitors for More Flexibility and Screen Space

Virtual Displays for Knowledge Work: Extending or Replacing ...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Leonardo Pavanatto Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech USA

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

In this paper, we explore the potential of virtual displays in sup-porting knowledge work, focusing on scenarios where conventional physical monitors fall short. Our research investigates the feasibility and productivity costs of extending or replacing physical monitors with augmented and virtual reality displays. We present three com-pelling use cases, illustrating how virtual displays enhance flexibility, adaptability, and customization in remote and diverse work settings. Lessons learned from user studies highlight hardware and interface design challenges, emphasizing the need for larger resolution and field of view in head-worn displays (HWD). We conclude the paper with research opportunities and a call to address the evolving demands of knowledge work interfaces.

关键词： Productivity Three-dimensional displays Head-mounted displays Focusing Virtual reality User interfaces Hardware

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Simulacrum of Stories: Examining Large Language Models as Qualitative Research Participants 25

Simulacrum of Stories: Examining Large Language Models as Qu...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Kapania, Shivani Agnew, William Eslami, Motahhare Heidari, Hoda Fox, Sarah E School of Computer Science Carnegie Mellon University Pittsburgh PA United States Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9798400713941

The recent excitement around generative models has sparked a wave of proposals suggesting the replacement of human participation and labor in research and development-e.g., through surveys, experiments, and interviews - with synthetic research data generated by large language models (LLMs). We conducted interviews with 19 qualitative researchers to understand their perspectives on this paradigm shift. Initially skeptical, researchers were surprised to see similar narratives emerge in the LLM-generated data when using the interview probe. However, over several conversational turns, they went on to identify fundamental limitations, such as how LLMs foreclose participants' consent and agency, produce responses lacking in palpability and contextual depth, and risk delegitimizing qualitative research methods. We argue that the use of LLMs as proxies for participants enacts the surrogate effect, raising ethical and epistemological concerns that extend beyond the technical limitations of current models to the core of whether LLMs fit within qualitative ways of knowing. © 2025 Copyright held by the owner/author(s).

关键词： large language models LLM agents LLMs in qualitative research qualitative research simulating research participants synthetic research data synthetic users

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Exploring Effect of Level of Storytelling Richness on science Learning in Interactive and Immersive Virtual Reality 22

Exploring Effect of Level of Storytelling Richness on Scienc...

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2022 ACM International Conference on Interactive Media Experiences, IMX 2022

作者： Zhang, Lei A. Bowman, Doug Human-Centered Design Virginia Tech United States Center for Human Computer Interaction Virginia Tech Computer Science United States

ISBN: (纸本)9781450392129

Immersive and interactive storytelling in virtual reality (VR) is an emerging creative practice that has been thriving in recent years. Educational applications using immersive VR storytelling to explain complex science concepts have very promising pedagogical benefits because on the one hand, storytelling breaks down the complexity of science concepts by bridging them to people's everyday experiences and familiar cognitive models, and on the other hand, the learning process is further reinforced through rich interactivity afforded by the VR experiences. However, it is unclear how different amounts of storytelling in an interactive VR storytelling experience may affect learning outcomes due to a paucity of literature on educational VR storytelling research. This preliminary study aims to add to the literature through an exploration of variations in the designs of essential storytelling elements in educational VR storytelling experiences and their impact on the learning of complex immunology concepts. © 2022 ACM.

关键词： Virtual reality

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Benefits of Machine Learning Explanations: Improved Learning in an AI-assisted Sequence Prediction Task 25

Benefits of Machine Learning Explanations: Improved Learning...

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30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Liang, Yu Collaris, Dennis Willemsen, Martijn C. Van Wijk, Jarke J. Human-Technology Interaction Eindhoven University of Technology Eindhoven Netherlands Dept. Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands Jheronimus Academy of Data Science Den Bosch Netherlands

ISBN: (纸本)9798400713064

Research in Explainable AI (XAI) has shown that explanations can improve users' understanding of AI models, improve user performance and potentially reduce overreliance on AI predictions. However, this is mostly evaluated by static rather than dynamic measures, and the role of XAI on learning over trials is rarely studied. In this study, we use a context-free sequence prediction task, in which 458 participants predict the next symbol in a fixed sequence (with some noise) over 80 trials. We compare performance with AI and XAI advice against no AI support, and subsequently we test for learning by taking away the AI support after 40 trials (i.e., a reversal study design). Our results show that users learn faster with XAI than with AI without explanations or no AI and are better able to recover in performance from the removal of AI. However, the benefits of XAI on learning are much smaller for more difficult tasks. This work demonstrates the benefits of repeated measures user studies and multilevel modeling to better understand learning processes in XAI. It also shows the potential of AI explanations to help users to learn and poses XAI design suggestions to support learning in human-AI collaboration. © 2025 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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