Journal: Proceedings of the ACM on Human-Computer Interaction

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Association for Computing Machinery

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ISSN

2573-0142

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2022 - 20259
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Publications 1 - 9 of 9
  • Typing Behavior is About More than Speed: Users' Strategies for Choosing Word Suggestions Despite Slower Typing Rates
    Item type: Journal Article
    Lehmann, Florian; Kornecki, Itto; Buschek, Daniel; et al. (2023)
    Proceedings of the ACM on Human-Computer Interaction
    Mobile word suggestions can slow down typing, yet are still widely used. To investigate the apparent benefits beyond speed, we analyzed typing behavior of 15,162 users of mobile devices. Controlling for natural typing speed (a confounding factor not considered by prior work), we statistically show that slower typists use suggestions more often but are slowed down by doing so. To better understand how these typists leverage suggestions - if not to improve their speed - we extract eight usage strategies, including completion, correction, and next-word prediction. We find that word characteristics, such as length or frequency, along with the strategy, are predictive of whether a user will select a suggestion. We show how to operationalize our findings by building and evaluating a predictive model of suggestion selection. Such a model could be used to augment existing suggestion algorithms to consider people's strategic use of word predictions beyond speed and keystroke savings.
  • Emotionally Aware Moderation: The Potential of Emotion Monitoring in Shaping Healthier Social Media Conversations
    Item type: Journal Article
    Su , Xiaotian; Zierau , Naim; Kim , Soomin; et al. (2025)
    Proceedings of the ACM on Human-Computer Interaction
    Social media platforms increasingly employ proactive moderation techniques, such as detecting and curbing toxic and uncivil comments, to prevent the spread of harmful content. Despite these efforts, such approaches are often criticized for creating a climate of censorship and failing to address the underlying causes of uncivil behavior. Our work makes both theoretical and practical contributions by proposing and evaluating two types of emotion monitoring dashboards to enhance users’ emotional awareness and mitigate hate speech. In a study involving 211 participants, we evaluate the effects of the two mechanisms on user commenting behavior and emotional experiences. The results reveal that these interventions effectively increase users’ awareness of their emotional states and reduce hate speech. However, our findings also indicate potential unintended effects, including increased expression of negative emotions (Angry, Fear, and Sad) when discussing sensitive issues. These insights provide a basis for further research on integrating proactive emotion regulation tools into social media platforms to foster healthier digital interactions.
  • MARLUI: Multi-Agent Reinforcement Learning for Adaptive Point-and-Click UIs
    Item type: Journal Article
    Langerak, Thomas; Christen, Sammy; Albaba, Mert; et al. (2024)
    Proceedings of the ACM on Human-Computer Interaction
    As the number of selectable items increases, point-and-click interfaces rapidly become complex, leading to a decrease in usability. Adaptive user interfaces can reduce this complexity by automatically adjusting an interface to only display the most relevant items. A core challenge for developing adaptive interfaces is to infer user intent and chose adaptations accordingly. Current methods rely on tediously hand-crafted rules or carefully collected user data. Furthermore, heuristics need to be recrafted and data regathered for every new task and interface. To address this issue, we formulate interface adaptation as a multi-agent reinforcement learning problem. Our approach learns adaptation policies without relying on heuristics or real user data, facilitating the development of adaptive interfaces across various tasks with minimal adjustments needed. In our formulation, a user agent mimics a real user and learns to interact with an interface via point-and-click actions. Simultaneously, an interface agent learns interface adaptations, to maximize the user agent's efficiency, by observing the user agent's behavior. For our evaluation, we substituted the simulated user agent with actual users. Our study involved twelve participants and concentrated on automatic toolbar item assignment. The results show that the policies we developed in simulation effectively apply to real users. These users were able to complete tasks with fewer actions and in similar times compared to methods trained with real data. Additionally, we demonstrated our method's efficiency and generalizability across four different interfaces and tasks.
  • PACMHCI V8, ETRA, May 2024 Editorial
    Item type: Other Journal Item
    Duchowski, Andrew T.; Kiefer, Peter; Krejtz, Krzysztof; et al. (2024)
    Proceedings of the ACM on Human-Computer Interaction
  • Narratives of War: Ukrainian Memetic Warfare on Twitter
    Item type: Journal Article
    Mejova, Yelena; Capozzi, Arthur; Monti, Corrado; et al. (2025)
    Proceedings of the ACM on Human-Computer Interaction
    The 2022 Russian invasion of Ukraine has seen an intensification in the use of social media by governmental actors in cyber warfare. Wartime communication via memes has been a successful strategy used not only by independent accounts such as @uamemesforces, but also -for the first time in a full-scale interstate war - by official Ukrainian government accounts such as @Ukraine and @DefenceU. We study this prominent example of memetic warfare through the lens of its narratives, and find them to be a key component of success: tweets with a 'victim' narrative garner twice as many retweets. However, malevolent narratives focusing on the enemy resonate more than those about heroism or victims with countries providing more assistance to Ukraine. Our findings present a nuanced examination of Ukraine's influence operations and of the worldwide response to it, thus contributing new insights into the evolution of socio-technical systems in times of war.
  • PACMHCI V9, N3, May 2025 Editorial
    Item type: Other Journal Item
    Castner, Nora Jane; Kiefer, Peter; Laubrock, Jochen; et al. (2025)
    Proceedings of the ACM on Human-Computer Interaction
    This special issue of the Proceedings of the ACM on Human-Computer Interaction includes accepted full papers from the ACM Symposium on Eye Tracking Research and Applications (ETRA). ETRA is the premier eye-tracking conference that brings together researchers from across disciplines to present advances in eye-tracking systems and methods, oculomotor research, eye movement data analysis, gaze-based interaction, and eye-tracking applications. A total of 24 full papers were accepted from 80 submissions after a rigorous reviewing process (30% acceptance rate). Accepted contributions were split into special issues in two journals, depending on the fit of topic and authors' preferences. 16 accepted papers are included in this issue of the Proceedings of the ACM on Human-Computer Interaction. 8 will be published in the Proceedings of the ACM on Computer Graphics and Interactive Techniques. All accepted papers are invited to present at ETRA 2025 (May 26 - May 29, 2025, in Tokyo). We would like to thank all members of the Editorial Board and all external reviewers for their effort and dedication, as well as all authors for their high-quality contributions.
  • ViGather: Inclusive Virtual Conferencing with a Joint Experience Across Traditional Screen Devices and Mixed Reality Headsets
    Item type: Journal Article
    Qiu, Huajian; Streli, Paul; Luong, Tiffany; et al. (2023)
    Proceedings of the ACM on Human-Computer Interaction
    Teleconferencing is poised to become one of the most frequent use cases of immersive platforms, since it supports high levels of presence and embodiment in collaborative settings. On desktop and mobile platforms, teleconferencing solutions are already among the most popular apps and accumulate significant usage time - -not least due to the pandemic or as a desirable substitute for air travel or commuting. In this paper, we present ViGather, an immersive teleconferencing system that integrates users of all platform types into a joint experience via equal representation and a first-person experience. ViGather renders all participants as embodied avatars in one shared scene to establish co-presence and elicit natural behavior during collocated conversations, including nonverbal communication cues such as eye contact between participants as well as body language such as turning one's body to another person or using hand gestures to emphasize parts of a conversation during the virtual hangout. Since each user embodies an avatar and experiences situated meetings from an egocentric perspective no matter the device they join from, ViGather alleviates potential concerns about self-perception and appearance while mitigating potential 'Zoom fatigue', as users' self-views are not shown. For participants in Mixed Reality, our system leverages the rich sensing and reconstruction capabilities of today's headsets. For users of tablets, laptops, or PCs, ViGather reconstructs the user's pose from the device's front-facing camera, estimates eye contact with other participants, and relates these non-verbal cues to immediate avatar animations in the shared scene. Our evaluation compared participants' behavior and impressions while videoconferencing in groups of four inside ViGather with those in Meta Horizon as a baseline for a social VR setting. Participants who participated on traditional screen devices (e.g., laptops and desktops) using ViGather reported a significantly higher sense of physical, spatial, and self-presence than when using Horizon, while all perceived similar levels of active social presence when using Virtual Reality headsets. Our follow-up study confirmed the importance of representing users on traditional screen devices as reconstructed avatars for perceiving self-presence.
  • Gay Dating on Non-dating Platforms: The Case of Online Dating Activities of Gay Men on a Q&A Platform
    Item type: Conference Paper
    Wang, Ye; Lu, Zhicong; Wattenhofer, Roger (2022)
    Proceedings of the ACM on Human-Computer Interaction
    Gay dating applications, such as Grindr and SCRUFF, are considered the primary platforms for gay men to conduct online dating activities. However, on Zhihu, a Chinese question-and-answer website, tens of thousands of homosexual users have been searching for romantic partners, which suggests that Zhihu may have unique affordances in online dating activities for Chinese gay men. To better understand how Chinese gay men perceive the affordances of a non-dating platform for online dating, we conduct a mixed-methods study, including observations, interviews, and quantitative and qualitative analysis of users' self-presentations. We find that gay men users publish personal ads by answering "fishing questions" on Zhihu. Through our analysis, we examine how users perceive the affordances of Zhihu to satisfy their social and psychological gratifications at the self, community, and audience levels. Although gay users face the risk of disclosing homosexual identity on mainstream social media, they perceive such risk as acceptable for better online dating experience. We discuss how users respond to severe social stigma in China, and the gap between user needs and the design of gay dating applications. We elaborate on the implications of our findings to discuss the potential benefits for LGBTQ users if LGBTQ service providers collaborate with social media.
  • Ubiquitous Machinery Monitoring – A Field Study on Manufacturing Workers’ User Experience of Mobile and Wearable Monitoring Apps
    Item type: Journal Article
    Müller, Sebastian; Baldauf, Matthias; Seeliger, Arne (2022)
    Proceedings of the ACM on Human-Computer Interaction
    Fueled by ongoing digitization efforts, manufacturing is currently undergoing a transformational process towards interconnected machinery and workforce, which enables a wide range of interactive monitoring and controlling applications. Whereas existing user-centered work addressed remote monitoring from office workplaces, it remains unclear how manufacturing workers experience and adopt machinery monitoring apps on mobile and wearable devices. To close this gap, we conducted a four-week field study in a running factory to study workers’ overall user experience and acceptance of such monitoring apps, the subjective impact on their work routines, and their preferred device type. Under productive operation, 11 manufacturing workers used functional application prototypes on smartphones and smartwatches to receive notifications of machine incidents. In 22 individual interviews and two focus groups, we collected the participants’ impressions and assessments. Based on these results, we derive a set of recommendations for designing and deploying machinery monitoring apps for manufacturing workers.
Publications 1 - 9 of 9