Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Identity Decolonization as Reclaiming Narrative Agency: Identity Work of Bengali Communities on Quora

While people’s identities can be marginalized through various forces, colonialism is one of the primary ways that continues to influence people’s lives and identities. Colonialism refers to the policies and practices where foreign powers migrate to other lands and alter the social structures, and thus identities, of local populations. What is less understood is how online spaces can support people in the aftermath of colonization in revising, repairing, and strengthening their identities—the process of identity decolonization work. Using trace ethnography beginning on 15 May, 2020 and ending on 15 July, 2020 and drawing on Poka Laenui’s framework of decolonization, we explore how South Asian Bengalis on the platform Bengali Quora (BnQuora) engage in collaborative identity decolonization work to reclaim narrative agency. We discuss how narratives serve to help people bounce back from threat or vulnerability—a concept we dub narrative resilience. We also describe potential implications for future scholarship focused on decolonization that extends multiple ongoing conversations around ICT for development, social justice, decolonial HCI, and identity research within the CHI community.
More than Bedtime and the Bedroom: Sleep Management as a Collaborative Work for the Family

Sleep is a vital health issue. Continued sleep deficiency can increase the chance of stroke, cardiovascular disease, obesity, and diabetes. Previous studies have investigated sleep as an individual activity performed within bedrooms at night. In this study with twenty parents of young children, we identify sleep as a complex experience entangled with social dynamics between family members. For example, children's sleep means not just time for children to rest, but time for self-care for parents. This paper's contributions are twofold. First, we show how the boundaries that define sleep in terms of time (at night), space (in bedrooms), and unit of analysis (individual-focused) limit designers' opportunities to tackle the deeper sleep issues of families. Second, we suggest "division of labor" as an important but rarely discussed design concept to enhance family sleep, and as a design theme for home technologies that address issues emerging from social dynamics between householders.
Anticipate and Adjust: Cultivating Access in Human-Centered Methods

Methods are fundamental to doing research and can directly impact who is included in scientific advances. Given accessibility research's increasing popularity and pervasive barriers to conducting and participating in research experienced by people with disabilities, it is critical to ask how methods are made accessible. Yet papers rarely describe their methods in detail. This paper reports on 17 interviews with accessibility experts about how they include both facilitators and participants with disabilities in popular user research methods. Our findings offer strategies for anticipating access needs while remaining flexible and responsive to unexpected access barriers. We emphasize the importance of considering accessibility at all stages of the research process, and contextualize access work in recent disability and accessibility literature. We explore how technology or processes could reflect a norm of accessibility. Finally, we discuss how various needs intersect and conflict and offer a practical structure for planning accessible research.
(Re)discovering the Physical Body Online: Strategies and Challenges to Approach Non-Cisgender Identity in Social Virtual Reality

The contemporary understanding of gender continues to highlight the complexity and variety of gender identities beyond a binary dichotomy regarding one’s biological sex assigned at birth. The emergence and popularity of various online social spaces also makes the digital presentation of gender even more sophisticated. In this paper, we use non-cisgender as an umbrella term to describe diverse gender identities that do not match people’s sex assigned at birth, including Transgender, Genderfluid, and Non-binary. We especially explore non-cisgender individuals’ identity practices and their challenges in novel social Virtual Reality (VR) spaces where they can present, express, and experiment their identity in ways that traditional online social spaces cannot provide. We provide one of the first empirical evidence of how social VR platforms may introduce new and novel phenomena and practices of approaching diverse gender identities online. We also contribute to re-conceptualizing technology-supported identity practices by highlighting the role of (re)discovering the physical body online and informing the design of the emerging metaverse for supporting diverse gender identities in the future.
Supporting the Contact Tracing Process with WiFi Location Data: Opportunities and Challenges

Contact tracers assist in containing the spread of highly infectious diseases such as COVID-19 by engaging community members who receive a positive test result in order to identify close contacts. Many contact tracers rely on community member’s recall for those identifications, and face limitations such as unreliable memory. To investigate how technology can alleviate this challenge, we developed a visualization tool using de-identified location data sensed from campus WiFi and provided it to contact tracers during mock contact tracing calls. While the visualization allowed contact tracers to find and address inconsistencies due to gaps in community member’s memory, it also introduced inconsistencies such as false-positive and false-negative reports due to imperfect data, and information sharing hesitancy. We suggest design implications for technologies that can better highlight and inform contact tracers of potential areas of inconsistencies, and further present discussion on using imperfect data in decision making.
Sufficient Conditions for Optimality and Asymptotic Stability in Two-Player Zero-Sum Hybrid Games

In this paper, we formulate a two-player zero-sum game under dynamic constraints given in terms of hybrid dynamical systems. We present sufficient conditions with Hamilton-Jacobi-Isaacs-like equations to guarantee attaining a solution to the game. It is shown that when the players select the optimal strategy, the value function can be evaluated without the need of computing solutions. Under additional conditions, we show that the optimal feedback laws render a set of interest asymptotically stable. Using this framework, we address an optimal control problem under the presence of an adversarial action in which the decision-making agents have dynamics that might exhibit both continuous and discrete behavior. Applications of this problem, as presented here, include disturbance rejection and security scenarios, for which the effect of the worst-case adversarial action is minimized.
Virfie: Virtual Group Selfie Station for Remote Togetherness

Selfies have become a prominent means of online communication. Group selfies, in particular, encourage people to represent their identity as part of the group and foster a sense of belonging. During the COVID-19 pandemic, video conferencing systems are used as a tool for group selfies. However, conventional systems are not ideal for group selfies due to the rigidness of grid-based layout, information overload, and lack of eye contact. To explore design opportunities and needs for a novel virtual group selfie platform, we conducted a participatory design, and identified three characteristics of virtual group selfie scenarios, “context with narratives”, “interactive group tasks”, and “capturing subtle moments. ” We implemented Virfie, a web-based platform that enables users to take group selfies with embodied social interaction, and to create and customize selfie scenarios using a novel JSON specification. In order to validate our design concept and identify usability issues we conducted a user study. Feedbacks from the study participants suggest that Virfie is effective at strengthening social interaction and remote togetherness.
AlgoSolve: Supporting Subgoal Learning in Algorithmic Problem-Solving with Learnersourced Microtasks

Designing solution plans before writing code is critical for successful algorithmic problem-solving. Novices, however, often plan on-the-fly during implementation, resulting in unsuccessful problem-solving due to lack of mental organization of the solution. Research shows that subgoal learning helps learners develop more complete solution plans by enhancing their understanding of the high-level solution structure. However, expert-created materials such as subgoal labels are necessary to provide learning benefits from subgoal learning, which are a scarce resource in self-learning due to limited availability and high cost. We propose a learnersourcing workflow that collects high-quality subgoal labels from learners by helping them improve their label quality. We implemented the workflow into AlgoSolve, a prototype interface that supports subgoal learning for algorithmic problems. A between-subjects study with 63 problem-solving novices revealed that AlgoSolve helped learners create higher-quality labels and more complete solution plans, compared to a baseline method known to be effective in subgoal learning.
For What It’s Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems

As algorithms are increasingly augmenting and substituting human decision-making, understanding how the introduction of computational agents changes the fundamentals of human behavior becomes vital. This pertains to not only users, but also those parties who face the consequences of an algorithmic decision. In a controlled experiment with 480 participants, we exploit an extended version of two-player ultimatum bargaining where responders choose to bargain with either another human, another human with an AI decision aid or an autonomous AI-system acting on behalf of a passive human proposer. Our results show strong responder preferences against the algorithm, as most responders opt for a human opponent and demand higher compensation to reach a contract with autonomous agents. To map these preferences to economic expectations, we elicit incentivized subject beliefs about their opponent’s behavior. The majority of responders maximize their expected value when this is line with approaching the human proposer. In contrast, responders predicting income maximization for the autonomous AI-system overwhelmingly override economic self-interest to avoid the algorithm.
Watch Your Flavors: Augmenting People’s Flavor Perceptions and Associated Emotions based on Videos Watched while Eating

People engage in different activities while eating alone, such as watching television or scrolling through social media on their phones. However, the impacts of these visual contents on human cognitive processes, particularly related to flavor perception and its attributes, are still not thoroughly explored. This paper presents a user study to evaluate the influence of six different types of video content (including nature, cooking, and a new food video genre known as mukbang) on people’s flavor perceptions in terms of taste sensations, liking, and emotions while eating plain white rice. Our findings revealed that the participants’ flavor perceptions are augmented based on different video content, indicating significant differences in their perceived taste sensations (e.g., increased perception of salty and spicy sensations). Furthermore, potential future implications are revealed to promote digital commensality and healthier eating habits.
Design is Worth a Thousand Words: The Effect of Digital Interaction Design on Picture-Prompted Reminiscence

Interactions with our personal and family pictures are essential to continued social reminiscence, leading to long-term benefits, including reduced social isolation. Previous research has identified how designs of digital picture tools fall short of physical options specifically in terms of reminiscence. However, the relative prompting abilities of different digital interactions, including the types of memories prompted like external facts or person-centred memories, have not yet been explored. To investigate this, we present a controlled study of the memories prompted by three digital picture interactions (slideshow, gallery, and tabletop) on personal touchscreen devices. We find differences in how these tools and the interactions they support prompt reminiscence. In particular, gallery views prompt significantly fewer memories than either the tabletop or slideshow. Slideshows prompt significantly more external, factual memories, but not more person-centred memories, which are key to reminiscence. This has implications for the overall social usability of digital picture interactions.
To Self-Persuade or be Persuaded: Examining Interventions for Users’ Privacy Setting Selection

User adoption of security and privacy (S&P) best practices remains low, despite sustained efforts by researchers and practitioners. Social influence is a proven method for guiding user S&P behavior, though most work has focused on studying peer influence, which is only possible with a known social graph. In a study of 104 Facebook users, we instead demonstrate that crowdsourced S&P suggestions are significantly influential. We also tested how reflective writing affected participants’ S&P decisions, with and without suggestions. With reflective writing, participants were less likely to accept suggestions — both social and Facebook default suggestions. Of particular note, when reflective writing participants were shown the Facebook default suggestion, they not only rejected it but also (unknowingly) configured their settings in accordance with expert recommendations. Our work suggests that both non-personal social influence and reflective writing can positively influence users’ S&P decisions, but have negative interactions.
Understanding Emotion Changes in Mobile Experience Sampling

Mobile experience sampling methods (ESMs) are widely used to measure users’ affective states by randomly sending self-report requests. However, this random probing can interrupt users and adversely influence users’ emotional states by inducing disturbance and stress. This work aims to understand how ESMs themselves may compromise the validity of ESM responses and what contextual factors contribute to changes in emotions when users respond to ESMs. Towards this goal, we analyze 2,227 samples of the mobile ESM data collected from 78 participants. Our results show ESM interruptions positively or negatively affected users’ emotional states in at least 38% of ESMs, and the changes in emotions are closely related to the contexts users were in prior to ESMs. Finally, we discuss the implications of using the ESM and possible considerations for mitigating the variability in emotional responses in the context of mobile data collection for affective computing.
Increasing Socio-Spatial Connectedness Among Students: A Location-Based AR Social Media Network Approach

Augmented Reality (AR) applications embedding user-generated social media content into the physical environment have the potential to increase users’ socio-spatial connectedness but are under-researched. Therefore, we built a location-based AR social network app, including geotagged AR social media photos. We explore our app in a research probe of senior university students (n = 6), providing activity-related information to first-year university students at the campus (n = 11). We could identify how AR content is created at a location, what type of pictures are shared with whom, how the sharing increased the attachment to local places and the socio-spatial connectedness for first-year students. Finally, we discuss other application scenarios and outline challenges and opportunities for location-based AR social media networks.
Electrical Head Actuation: Enabling Interactive Systems to Directly Manipulate Head Orientation

We propose a novel interface concept in which interactive systems directly manipulate the user's head orientation. We implement this using electrical-muscle-stimulation (EMS) of the neck muscles, which turns the head around its yaw (left/right) and pitch (up/down) axis. As the first exploration of EMS for head actuation, we characterized which muscles can be robustly actuated. Second, we evaluated the accuracy of our system for actuating participants' head orientation towards static targets and trajectories. Third, we demonstrated how it enables interactions not possible before by building a range of applications, such as (1) synchronizing head orientations of two users, which enables a user to communicate head nods to another user while listening to music, and (2) directly changing the user's head orientation to locate objects in AR. Finally, in our second study, participants felt that our head actuation contributed positively to their experience in four distinct applications.
AI-Moderated Decision-Making: Capturing and Balancing Anchoring Bias in Sequential Decision Tasks

Decision-making involves biases from past experiences, which are difficult to perceive and eliminate. We investigate a specific type of anchoring bias, in which decision-makers are anchored by their own recent decisions, e.g. a college admission officer sequentially reviewing students. We propose an algorithm that identifies existing anchored decisions, reduces sequential dependencies to previous decisions, and mitigates decision inaccuracies post-hoc with 2% increased agreement to ground-truth on a large-scale college admission decision data set. A crowd-sourced study validates this algorithm on product preferences (5% increased agreement). To avoid biased decisions ex-ante, we propose a procedure that presents instances in an order that reduces anchoring bias in real-time. Tested in another crowd-sourced study, it reduces bias and increases agreement to ground-truth by 7%. Our work reinforces individuals with similar characteristics to be treated similarly, independent of when they were reviewed in the decision-making process.
A New Uncanny Valley? The Effects of Speech Fidelity and Human Listener Gender on Social Perceptions of a Virtual-Human Speaker

Virtual humans can be used to deliver persuasive arguments; yet, those with synthetic text-to-speech (TTS) have been perceived less favorably than those with recorded human speech. In this paper, we investigate standard concatenative TTS and more advanced neural TTS. We conducted a 3x2 between-subjects experiment (n=79) to evaluate the effect of a virtual human’s speech fidelity at three levels (Standard TTS, Neural TTS, and Human speech) and the listener’s gender (male or female) on perceptions and persuasion. We found that the virtual human was perceived as significantly less trustworthy by both genders, if they used neural TTS compared to human speech, while male listeners (but not females) also perceived standard TTS as less trustworthy than human speech. Our findings indicate that neural TTS may not be an effective choice for persuasive virtual humans and that gender of the listener plays a role in how virtual humans are perceived.
Paracentral and near-peripheral visualizations: Towards attention-maintaining secondary information presentation on OHMDs during in-person social interactions

Optical see-through Head-Mounted Displays (OST HMDs, OHMDs) are known to facilitate situational awareness while accessing secondary information. However, information displayed on OHMDs can cause attention shifts, which distract users from natural social interactions. We hypothesize that information displayed in paracentral and near-peripheral vision can be better perceived while the user is maintaining eye contact during face-to-face conversations. Leveraging this idea, we designed a circular progress bar to provide progress updates in paracentral and near-peripheral vision. We compared it with textual and linear progress bars under two conversation settings: a simulated one with a digital conversation partner and a realistic one with a real partner. Results show that a circular progress bar can effectively reduce notification distractions without losing eye contact and is more preferred by users. Our findings highlight the potential of utilizing the paracentral and near-peripheral vision for secondary information presentation on OHMDs.
Templates and Trust-o-meters: Towards a widely deployable indicator of trust in Wikipedia

The success of Wikipedia and other user-generated content communities has been driven by the openness of recruiting volunteers globally, but this openness has also led to a persistent lack of trust in its content. Despite several attempts at developing trust indicators to help readers more quickly and accurately assess the quality of content, challenges remain for practical deployment to general consumers. In this work we identify and address three key challenges: empirically determining which metrics from prior and existing community approaches most impact reader trust; 2) validating indicator placements and designs that are both compact yet noticed by readers; and 3) demonstrating that such indicators can not only lower trust but also increase perceived trust in the system when appropriate. By addressing these, we aim to provide a foundation for future tools that can practically increase trust in user generated content and the sociotechnical systems that generate and maintain them.
Crowdworkers’ Temporal Flexibility is Being Traded for the Convenience of Requesters Through 19 ‘Invisible Mechanisms’ Employed by Crowdworking Platforms: A Comparative Analysis Study of Nine Platforms

Crowdworking platforms are a prime example of a product that sells flexibility to its consumers. In this paper, we argue that crowdworking platforms sell temporal flexibility to requesters to the detriment of workers. We begin by identifying a list of 19 features employed by crowdworking platforms that facilitate the trade of temporal flexibility from crowdworkers to requesters. Using the list of features, we conduct a comparative analysis of nine crowdworking platforms available to U.S.-based workers, in which we describe key differences and similarities between the platforms. We find that crowdworking platforms strongly favour features that promote requesters’ temporal flexibility over workers’ by limiting the predictability of workers’ working hours and restricting paid time. Further, we identify which platforms employ the highest number of features that facilitate the trade of temporal flexibility from workers to requesters, consequently increasing workers’ temporal precarity. We conclude the paper by discussing the implications of the results.
Exploring Situated & Embodied Support for Youth’s Mental Health: Design Opportunities for Interactive Tangible Device

The ability to manage emotions effectively is critical to healthy psychological and social development in youth. Prior work has focused on investigating the design of mental health technologies for this population, yet it is still unclear how to help them cope with emotionally difficult situations in-the-moment. In this paper, we aim to explore the appropriation, naturally emerging engagement patterns, and perceived psychological impact of an exemplar interactive tangible device intervention designed to provide in-situ support, when deployed with n=109 youth for 1.5 months. Our findings from semi-structured interviews and co-design workshops with a subset of participants (n=44 and n=25, respectively) suggest the potential of using technology-enabled objects to aid with down-regulation and self-compassion in moments of heightened emotion, to facilitate the practice of cognitive strategies, and to act as emotional companions. Lastly, we discuss design opportunities for integrating situated and embodied support in mental health interventions for youth.