bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-designing Mental Health Technologies with International University Students in Canada
Authors: Sien Sang-Wha , Ahn Jessica Y. , McGrenere Joanna
Published: October 2023

Mental health problems are a serious concern among university students, and international students in Canada are known to be particularly vulnerable due to the underutilization of mental health services and unfamiliarity with Western approaches to mental health. However, international students' mental well-being remains underexplored in HCI. In this study, we conducted remote synchronous remote co-design sessions with 19 participants (14 international students, 5 mental health professionals) to understand concretely what types of designs for interactive technologies suit these students' mental health needs and challenges. Based on their brainstormed ideas and sketches, we produced a set of design dimensions that span different types of support, interaction, and safety. The dimensions were then used to develop a set of four medium-fidelity mockups that spanned these dimensions, presenting a diverse range of design features. Using these mockups, we elicited feedback in an online survey from the same participants. Findings suggest that the students negotiate a complex understanding of helpfulness, comfort, and trust when they consider what types of designs to consider using. Each mockup highlights different ways to support individual differences and preferences. Our work serves as a foundation for designing technologies that can ease issues with accessibility and be more inclusive of international students' cultural backgrounds.
Competing Imaginaries and Partisan Divides in the Data Rhetoric of Advocacy Organizations
Authors: Darian Shiva , Dym Brianna , Voida Amy
Published: October 2023

Data are wielded to shape public opinion, particularly in electoral contexts where the role and veracity of information is questioned. This post-truth era is characterized by world events in which facts too often are obfuscated and evidential standards are abandoned. To study how data are used to influence pressing and divisive contemporary issues, this paper explores the rhetorical work that quantitative data are doing through the blogging practices of advocacy organizations during the highly-polarized month preceding the 2016 United States elections. We present results of a qualitative content analysis of the quantitative data used in 337 blog posts published by five pairs of conservative and liberal advocacy organizations over the course of the month leading up to the 2016 US elections. We identify key data rhetoric practices along partisan lines and contribute an analytic framework-evaluating ethos, pathos, and logos- that can be used to analyze the rhetorical use of data in other contexts. We then characterize two different imaginaries that come into conflict in this research: 1) the political imaginaries being promoted through organizational blogging and 2) the sociotechnical imaginary of the data economy, foregrounding differences in the epistemic value of data in each. We conclude by outlining research challenges and trajectories for future research within each of the two imaginaries of data.
Understanding Delay Awareness and Mitigation Mechanisms through an Iterative Design and Evaluation of a Prototype Alert System for Complex Teamwork
Authors: Zellner Katherine A. , Sarcevic Aleksandra , Krentsa Megan A. , Sullivan Travis M. , Burd Randall S.
Published: October 2023

Almost half of the preventable deaths in emergency care can be associated with a medical delay. Understanding how clinicians experience delays can lead to improved alert designs to increase delay awareness and mitigation. In this paper, we present the findings from an iterative user-centered design process involving 48 clinicians to develop a prototype alert system for supporting delay awareness in complex medical teamwork such as trauma resuscitation. We used semi-structured interviews and card-sorting workshops to identify the most common delays and elicit design requirements for the prototype alert system. We then conducted a survey to refine the alert designs, followed by near-live, video-guided simulations to investigate clinicians' reactions to the alerts. We contribute to CSCW by designing a prototype alert system to support delay awareness in time-critical, complex teamwork and identifying four mechanisms through which teams mitigate delays.
Cybersecurity, Safety, & Privacy Concerns of Student Support Structure for Information and Communication Technologies in Online Education
Authors: Tazi Faiza , Shrestha Sunny , Das Sanchari
Published: October 2023

COVID-19 has created a dramatic paradigm shift in education methods, which forced schools and universities to abandon the usual in-person education in favor of online education modules. Such a shift has extended the time and use of internet communication technologies (ICTs) by most, making online education platforms primary cyberattack targets. In this context, this study aims to explore parents, educators, and other caregivers' concerns about online education and the cybersecurity of their children and students. Thus, we conducted a survey-based study with 983 participants recruited through popular crowdsourcing platforms: MTurk and Prolific. Our results indicate a lack of technical support following cyber safety that the students received with the sudden transition to online education. Over 31% of our participants claimed that they never or rarely receive any communication related to cyber safety from the students' educational institutions. Additionally, our analysis shows that the student support structure needs to be trained and informed on the threats faced by children online and on the ways to mitigate these threats. Finally, we find a statistically significant difference between parents, educators, and other caregivers regarding their perceptions of children's online privacy and cyber safety. We conclude this work by providing actionable recommendations to promote privacy-preserving and digitally secure online education.
Digital Legacy: A Systematic Literature Review
Authors: Doyle Dylan Thomas , Brubaker Jed R.
Published: October 2023

To more effectively support the dying and bereaved in end-of-life contexts, over the past two decades HCI and social computing scholars have sought to understand digital legacy. In this paper, we argue that it is time to take stock of digital legacy scholarship, examining what we know, what gaps remain, and what areas are imperative for future work. Through a Grounded Theory Literature Review, we identify four foci in digital legacy research to date: how identity is navigated in the passing of digital legacy, how digital legacies are engaged with, how digital legacies are put to rest, and how technology interfaces with offline legacy technologies. Based on our analysis, we present a model depicting how digital legacy research examines a lifecycle of data as it is passed down. This model identifies that digital legacy data moves through three stages: encoding, accessing, and dispossessing. The model illustrates gaps in current research and charts possible inflection points for future social computing research. Specifically, we highlight the importance of multi-user and multi-generational networks of people in end-of-life scenarios. Additionally, the model exhibits emerging theoretical findings and major concepts in the nascent field of digital legacy research.
Evaluating Similarity Variables for Peer Matching in Digital Health Storytelling
Authors: Saksono Herman , Morris Vivien , Parker Andrea G. , Gajos Krzysztof Z.
Published: October 2023

Peer matching can enhance the impact of social health technologies. By matching similar peers, online health communities can optimally facilitate social modeling that supports positive health attitudes and moods. However, little work has examined how to operationalize similarities in digital health tools, thus limiting our ability to perform optimal peer matching. To address this gap, we conducted a factorial experiment to examine how three categories of similarity variables (i.e., Demographic, Ability, Experiential) can be used to perform peer matching that supports the social modeling of physical activity. We focus this study on physical activity because it is a health behavior that reduces the risk of chronic diseases. We also prioritized this study for single-caregiver mothers who often face substantial barriers to being active because of immense employment and household responsibilities, especially Black single-caregiver mothers. We recruited 309 single-caregiver mothers (49% Black, 51% white), then we asked them to listen to peer audio storytelling about family physical activity. We randomly matched/mismatched the storyteller's profile using the three categories of similarity variables. Our analyses demonstrated that matching by Demographic variables led to a significantly higher Physical Activity Intention. Furthermore, our subgroup analyses indicated that Black single-caregiver mothers experienced a significant and immediate effect of peer matching in Physical Activity Intention, Self-efficacy, and mood. In contrast, white single-caregiver mothers did not report any significant immediate effect. Collectively, our data suggest that peer matching in health storytelling is potentially beneficial for racially minoritized groups; and that having diverse representations in health technology is required for promoting health equity.
Exploring the Effects of Event-induced Sudden Influx of Newcomers to Online Pop Music Fandom Communities: Content, Interaction, and Engagement
Authors: Guo Qingyu , Shi Chuhan , Yin Zhuohao , Liu Chengzhong , Ma Xiaojuan
Published: October 2023

Online fandom communities (OFCs) provide a convenient space for fans to create, collect, and discuss the content of their mutual interest (e.g., music artists). Real-world events could frequently attract outsiders to join OFCs, providing both the opportunity to expand the fan base and challenges to manage the community. However, it is unclear that how influxes of newcomers would influence the development of OFCs and what user behaviors may be correlated with their future engagement. To fill this gap, we took the music OFCs as the focus, and quantitatively analyzed user behaviors and their correlations with users' future engagement in the community. Results suggested that 1) event-induced newcomers expressed more hate speech and negative sentiment, praised less celebrity-related content (e.g., song, album), and interacted with narrower cohorts than existing members; 2) Although existing members tended to receive more upvotes during the events than before and after the events, newcomers showed an opposite trend; 3) keeping users' activeness, expressing positive sentiments, and having diverse interactions during periods of influx were helpful when maintaining members' future levels of engagement. This work deepened the understanding of fan behaviors in the dynamic period, and we discussed how our insights could benefit OFCs.
Identity Struggles as Online Activism in China: A Case Study Based on "The Inviting Plan for 985 Fives" Community on Douban
Authors: Lei Qinyuan , Kuksenok Kit , Tang Ran , Guo Jingyi , Ji Ran , LI Jiaxun
Published: October 2023

Online communities support the well-being of their members by encouraging their social identity formation. In the context of an online community, online activism in the form of identity struggles can be particularly helpful for marginalized individuals or groups. Since May 2020, students from the 985 universities, an elite educational project in China, have been coming to an online community named "The Inviting Plan for 985 Fives" on Douban, an interest-based Social Network Site (SNS), to discuss their failure and dissatisfaction in life. Students who were once recognized for their academic excellence now identify as "fives" (or "garbage"). The present study examines how the Douban group, as a social network and collaborative system, supports the group members in their identity struggles in the context of increasingly fierce peer competition in China. We employ a qualitative approach, combining ethnographic methods such as participant observation and semi-structured interviews, with in-depth analysis of the top discussion threads. We discover that while peer competition and social stratification in contemporary China cause students at the top universities to feel anxious and lost, the online community they build collectively supports them to create a new social identity, the identity of "five," which is the basis of their online activism. Through this new identity, they seek unofficial democracy, civic participation, and possibilities of social change.
Increasing Participation in Peer Production Communities with the Newcomer Homepage
Authors: Warncke-Wang Morten , Ho Rita , Miller Marshall , Johnson Isaac
Published: October 2023

For peer production communities to be sustainable, they must attract and retain new contributors. Studies have identified social and technical barriers to entry and discovered some potential solutions, but these solutions have typically focused on a single highly successful community, the English Wikipedia, been tested in isolation, and rarely evaluated through controlled experiments. We propose the Newcomer Homepage, a central place where newcomers can learn how peer production works and find opportunities to contribute, as a solution for attracting and retaining newcomers. The homepage was built upon existing research and designed in collaboration with partner communities. Through a large-scale controlled experiment spanning 27 non-English Wikipedia wikis, we evaluate the homepage and find modest gains, and that having a positive effect on the newcomer experience depends on the newcomer's context. We discuss how this impacts interventions that aim to improve the newcomer experience in peer production communities.
Mechanisms of True and False Rumor Sharing in Social Media: Collective Intelligence or Herd Behavior?
Authors: Pröllochs Nicolas , Feuerriegel Stefan
Published: October 2023

Social media platforms disseminate extensive volumes of online content, including true and, in particular, false rumors. Previous literature has studied the diffusion of offline rumors, yet more research is needed to understand the diffusion of online rumors. In this paper, we examine the role of lifetime and crowd effects in social media sharing behavior for true vs. false rumors. Based on 126,301 Twitter cascades, we find that the sharing behavior is characterized by lifetime and crowd effects that explain differences in the spread of true as opposed to false rumors. All else equal, we find that a longer lifetime is associated with less sharing activities, yet the reduction in sharing is larger for false than for true rumors. Hence, lifetime is an important determinant explaining why false rumors die out. Furthermore, we find that the spread of false rumors is characterized by herding tendencies (rather than collective intelligence), whereby the spread of false rumors becomes proliferated at a larger cascade depth. These findings explain differences in the diffusion dynamics of true and false rumors and further offer practical implications for social media platforms.
MirrorUs: Mirroring Peers' Affective Cues to Promote Learner's Meta-Cognition in Video-based Learning
Authors: Chen Si , Situ Jason , Cheng Haocong , Kirst Desirée , Huang Yun
Published: October 2023

Learners' awareness of their own affective states (emotions) can improve their meta-cognition, which is a critical skill of being aware of and controlling one's cognitive, motivational, and affect, and adjusting their learning strategies and behaviors accordingly. To investigate the effect of peers' affects on learners' meta-cognition, we proposed two types of cues that aggregated peers' affects that were recognized via facial expression recognition:Locative cues (displaying the spikes of peers' emotions along a video timeline) andTemporal cues (showing the positivities of peers' emotions at different segments of a video). We conducted a between-subject experiment with 42 college students through the use of think-aloud protocols, interviews, and surveys. Our results showed that the two types of cues improved participants' meta-cognition differently. For example, interacting with theTemporal cues triggered the participants to compare their own affective responses with their peers and reflect more on why and how they had different emotions with the same video content. While the participants perceived the benefits of using AI-generated peers' cues to improve their awareness of their own learning affects, they also sought more explanations from their peers to understand the AI-generated results. Our findings not only provide novel design implications for promoting learners' meta-cognition with privacy-preserved social cues of peers' learning affects, but also suggest an expanded design framework for Explainable AI (XAI).
"I Want to Reveal, but I Also Want to Hide" Understanding the Conflict of Revealing and Hiding Needs in Virtual Study Rooms
Authors: Cho Soobin , Lee Joongseek , Suh Bongwon
Published: October 2023

Since the COVID-19 pandemic, video conferencing platforms have given rise to new virtual activities, such as virtual study rooms where users utilize video to share ambient presence for study motivation. In virtual study rooms, it can be challenging for the users to determine what to reveal and what to hide on camera, as the video needs to strongly convey their presence without revealing more than necessary. In this paper, we investigate the conflicting needs of virtual study room users to reveal and hide on camera, as well as the methods they employ to cope with these needs using videos. To this end, we conducted a three-step qualitative study. The first study involved interviews to discover the key user needs that entail the conflict to reveal and hide. The second study utilized virtual study room screen analysis to identify the video features that characterize virtual study room videos. In the last study, we employed interviews to associate the video features with the key user needs. Based on these findings, we discussed the effects of studying together that could be applied to a non-physical and non-interactive co-studying environment and the need for further development of video conferencing tools to effectively share ambient presence.
"Nip it in the Bud": Moderation Strategies in Open Source Software Projects and the Role of Bots
Authors: Hsieh Jane , Kim Joselyn , Dabbish Laura , Zhu Haiyi
Published: October 2023

Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and moderation, which is often supported by volunteer efforts. Moderation, as a non-technical form of labor, is a necessary but often overlooked task that maintainers undertake to sustain the community around an OSS project. This study examines the various structures and norms that support community moderation, describes the strategies moderators use to mitigate conflicts, and assesses how bots can play a role in assisting these processes. We interviewed 14 practitioners to uncover existing moderation practices and ways that automation can provide assistance. Our main contributions include a characterization of moderated content in OSS projects, moderation techniques, as well as perceptions of and recommendations for improving the automation of moderation tasks. We hope that these findings will inform the implementation of more effective moderation practices in open source communities.
Composing Team Compositions: An Examination of Instructors' Current Algorithmic Team Formation Practices
Authors: Hastings Emily M. , Ojha Vidushi , Austriaco Benedict V. , Karahalios Karrie , Bailey Brian P.
Published: October 2023

Instructors using algorithmic team formation tools must decide which criteria (e.g., skills, demographics, etc.) to use to group students into teams based on their teamwork goals, and have many possible sources from which to draw these configurations (e.g., the literature, other faculty, their students, etc.). However, tools offer considerable flexibility and selecting ineffective configurations can lead to teams that do not collaborate successfully. Due to such tools' relative novelty, there is currently little knowledge of how instructors choose which of these sources to utilize, how they relate different criteria to their goals for the planned teamwork, or how they determine if their configuration or the generated teams are successful. To close this gap, we conducted a survey (N=77) and interview (N=21) study of instructors using CATME Team-Maker and other criteria-based processes to investigate instructors' goals and decisions when using team formation tools. The results showed that instructors prioritized students learning to work with diverse teammates and performed "sanity checks" on their formation approach's output to ensure that the generated teams would support this goal, especially focusing on criteria like gender and race. However, they sometimes struggled to relate their educational goals to specific settings in the tool. In general, they also did not solicit any input from students when configuring the tool, despite acknowledging that this information might be useful. By opening the "black box" of the algorithm to students, more learner-centered approaches to forming teams could therefore be a promising way to provide more support to instructors configuring algorithmic tools while at the same time supporting student agency and learning about teamwork.
Understanding Participation among Disabled Creators in Online Marketplaces
Authors: Borgos-Rodriguez Katya , Piper Anne Marie
Published: October 2023

Emerging social media platforms and online marketplaces introduce new ways for individuals to sell and distribute handmade or custom items. This new landscape of online tools has the potential to provide work opportunities for people who are excluded from traditional workplaces due to inaccessible environments and work expectations. The present study involves an analysis of the work practices of 44 disabled creators who sell and promote their goods via online marketplaces. Through an analysis of publicly available content on Etsy and social media platforms, complemented with semi-structured interviews with a subset of creators, we report on the ways disabled sellers create, share and provide support through their practices. Our analysis reveals that creators move their work to an online space seeking more accessible ways to earn income, yet find themselves navigating access barriers that are enacted through platform norms, reward structures and algorithms. We discuss how online marketplaces present unique opportunities and challenges to participation for people with disabilities.
AI Consent Futures: A Case Study on Voice Data Collection with Clinicians
Authors: Wilcox Lauren , Brewer Robin , Diaz Fernando
Published: October 2023

As new forms of data capture emerge to power new AI applications, questions abound about the ethical implications of these data collection practices. In this paper, we present clinicians' perspectives on the prospective benefits and harms of voice data collection during health consultations. Such data collection is being proposed as a means to power models to assist clinicians with medical data entry, administrative tasks, and consultation analysis. Yet, clinicians' attitudes and concerns are largely absent from the AI narratives surrounding these use cases, and the academic literature investigating them. Our qualitative interview study used the concept of an informed consent process as a type of design fiction, to support elicitation of clinicians' perspectives on voice data collection and use associated with a fictional, near-term AI assistant. Through reflexive thematic analysis of in-depth sessions with physicians, we distilled eight classes of potential risks that clinicians are concerned about, including workflow disruptions, self-censorship, and errors that could impact patient eligibility for services. We conclude with an in-depth discussion of these prospective risks, reflect on the use of the speculative processes that illuminated them, and reconsider evaluation criteria for AI-assisted clinical documentation technologies in light of our findings.
"Honestly, I Think TikTok has a Vendetta Against Black Creators": Understanding Black Content Creator Experiences on TikTok
Authors: Harris Camille , Johnson Amber Gayle , Palmer Sadie , Yang Diyi , Bruckman Amy
Published: October 2023

As video-sharing social-media platforms have increased in popularity, a 'creator economy' has emerged in which platform users make online content to share with wide audiences, often for profit. As the creator economy has risen in popularity, so have concerns of racism and discrimination on social media. Black content creators across multiple platforms have identified challenges with racism and discrimination, perpetuated by platform users, companies that collaborate with creators for sponsored content, and the algorithms governing these platforms. In this work, we provide a qualitative study of the experiences of Black content creators on one video-sharing platform, TikTok. We conduct 12 semi-structured interviews with Black TikTok content creators to understand their experiences, identify the challenges they face, and understand their perceptions of the platform. We find that some common challenges include: content moderation, monetization, harassment and bullying from viewers, lack of transparency of recommendation and filtering algorithms, and the perception that content from Black creators is treated unfairly by those algorithms. We then suggest design interventions to mitigate the challenges, bolster positive aspects, and overall cultivate an inclusive algorithmic experience for Black creators on TikTok
"Would I Feel More Secure With a Robot?": Understanding Perceptions of Security Robots in Public Spaces
Authors: Marcu Gabriela , Lin Iris , Williams Brandon , Robert Lionel P. , Schaub Florian
Published: October 2023

Robots are increasingly being deployed as security agents helping law enforcement in spaces such as streets, parks, or shopping malls. Unfortunately, the deployment of security robots is not without problems and controversies. For example, the New York Police Department canceled its contract with Boston Dynamics in response to backlash from their use of Digidog, an autonomous robotic dog, which sparked fears in the public. However, it is unclear to what extent affected communities have been involved in the design and deployment process of robots. This is problematic because, without input from community members in the processes of design and deployment, security robots are likely to not satisfy the concerns or safety needs of real communities. To gain deeper insight into people's perceptions of security robots - including both potential benefits and concerns - we conducted 17 semi-structured interviews addressing the following research questions: RQ1. What characteristics do people ascribe to security robots? RQ2. What expectations do people have about the function and role of security robots? RQ3. What are people's attitudes toward the use of security robots? Our study offers several contributions to the existing literature on security robots.
"We Don't Want a Bird Cage, We Want Guardrails": Understanding & Designing for Preventing Interpersonal Harm in Social VR through the Lens of Consent
Authors: Schulenberg Kelsea , Li Lingyuan , Lancaster Caitlin , Zytko Douglas , Freeman Guo
Published: October 2023

As social Virtual Reality (VR) grows in prevalence, new possibilities for embodied and immersive social interaction emerge, including varied forms of interpersonal harm. Yet, challenges remain regarding defining, identifying, and mitigating said harm in social VR. In this paper, we take an alternative approach to understanding and designing solutions for interpersonal harm in social VR through the lens of consent, which circumvents the lack of consensus and social norms on what should be defined as harm in social VR and reflects the embodied, immersive, and offline-world-like nature of harm in social VR. Through interviews with 39 social VR users, we offer one of the first empirical explorations on how social VR users understand consent as "boundaries," (re)purpose existing social VR features for practicing consent as "boundary setting," and envision the design of future consent mechanics in social VR to balance protection and interaction expectations to mitigate interpersonal harm as "boundary violations" in social VR. This work makes significant contributions to CSCW and HCI research by (1) uncovering how social VR users craft novel conceptualizations of consent as boundaries and harm as unwanted boundary violations, and (2) providing three foundational principles for designing future consent mechanics in social VR informed by actual social VR users.
Breaking the Silence: Investigating Which Types of Moderation Reduce Negative Effects of Sexist Social Media Content
Authors: Sasse Julia , Grossklags Jens
Published: October 2023

Sexist content is widespread on social media and can reduce women's psychological well-being and their willingness to participate in online discourse, making it a societal issue. To counter these effects, social media platforms employ moderators. To date, little is known about the effectiveness of different forms of moderation in creating a safe space and their acceptance, in particular from the perspective of women as members of the targeted group and users in general (rather than perpetrators). In this research, we propose that some common forms of moderation can be systematized along two facets of visibility, namely visibility of sexist content and of counterspeech. In an online experiment (N = 839), we manipulated these two facets and tested how they shaped social norms, feelings of safety, and intent to participate, as well as fairness, trustworthiness, and efficacy evaluations. In line with our predictions, deletion of sexist content - i.e., its invisibility - and (public) counterspeech - i.e., its visibility - against visible sexist content contributed to creating a safe space. Looking at the underlying psychological mechanism, we found that these effects were largely driven by changes in what was perceived normative in the presented context. Interestingly, deletion of sexist content was judged as less fair than counterspeech against visible sexist content. Our research contributes to a growing body of literature that highlights the importance of norms in creating safer online environments and provides practical implications for moderators for selecting actions that can be effective and accepted.
Cultivating a Team Mindset about Productivity with a Nudge: A Field Study in Hybrid Development Teams
Authors: Fritz Thomas , Lill Alexander , Meyer André N. , Murphy Gail C. , Howe Lauren
Published: October 2023

While there has been significant study of both individuals and teams of knowledge workers, research has focused largely on one or the other, with less focus on the interaction between the two. In this paper, we explore the tensions between the individual and their team, focusing on the choices an individual makes towards their own productivity versus their team's productivity. We developed a technology probe with a team nudge that fosters recurring reflection and prompts individuals to consider how their team helps them to be productive. We examined its impact through a longitudinal field study with 48 participants. We chose to undertake this study with software development teams as they are examples of knowledge workers who collaborate on a shared set of tasks with specific goals. Our exploration took place with hybrid development teams, which have increasingly become the norm. Our analysis of a total of 8338 hourly self-reports and 1389 daily diary entries found that the team nudge increased participants' productivity ratings and team awareness, led to participants spending more time on their own tasks, reshaped their perceptions of themselves and their team, yet, in general, did not increase team cohesion or affect well-being.
Cura: Curation at Social Media Scale
Authors: He Wanrong , Gordon Mitchell L. , Popowski Lindsay , Bernstein Michael S.
Published: October 2023

How can online communities execute a focused vision for their space? Curation offers one approach, where community leaders manually select content to share with the community. Curation enables leaders to shape a space that matches their taste, norms, and values, but the practice is often intractable at social media scale: curators cannot realistically sift through hundreds or thousands of submissions daily. In this paper, we contribute algorithmic and interface foundations enabling curation at scale, and manifest these foundations in a system called Cura. Our approach draws on the observation that, while curators' attention is limited, other community members' upvotes are plentiful and informative of curators' likely opinions. We thus contribute a transformer-based curation model that predicts whether each curator will upvote a post based on previous community upvotes. Cura applies this curation model to create a feed of content that it predicts the curator would want in the community. Evaluations demonstrate that the curation model accurately estimates opinions of diverse curators, that changing curators for a community results in clearly recognizable shifts in the community's content, and that, consequently, curation can reduce anti-social behavior by half without extra moderation effort. By sampling different types of curators, Cura lowers the threshold to genres of curated social media ranging from editorial groups to stakeholder roundtables to democracies.
Escaping the Walled Garden? User Perspectives of Control in Data Portability for Social Media
Authors: Jamieson Jack , Yamashita Naomi
Published: October 2023

Data portability--the capability to transfer one's data from one platform to another--has been described as an important tool for giving individuals more control over their data. It is defined in significant regulations such as the GDPR, and implemented by major online platforms. Unfortunately, there is a lack of research investigating internet users' perceptions and expectations of this technology in specific contexts, which is vital for building effective designs. One particularly important context for studying user perspectives is social media, since it is deeply embedded into daily life and is particularly complex regarding the value and portability of user data. This paper addresses that gap through a survey and interviews of social media users in the United States. We identify current attitudes and practices toward controlling their social media data, and examine participants' impressions about the extent to which data portability may enhance their control. Participants had generally favorable impressions, but had differing opinions about what forms of control are important and the extent to which those could be served by data portability. Based on the results, we propose future directions for improving users' control in the context of social media, such as fine-tuned filtering of data to be transferred and ways to coordinate transfers alongside social contacts.
Inform, Explain, or Control: Techniques to Adjust End-User Performance Expectations for a Conversational Agent Facilitating Group Chat Discussions
Authors: Do Hyo Jin , Kong Ha-Kyung , Tetali Pooja , Karahalios Karrie , Bailey Brian P.
Published: October 2023

A conversational agent (CA) effectively facilitates online group discussions at scale. However, users may have expectations about how well the CA would perform that do not match with the actual performance, compromising technology acceptance. We built a facilitator CA that detects a member who has low contribution during a synchronous group chat discussion and asks the person to participate more. We designed three techniques to set end-user expectations about how accurately the CA identifies an under-contributing member: 1)information: explicitly communicating the accuracy of the detection algorithm, 2)explanation: providing an overview of the algorithm and the data used for the detection, and 3)adjustment: enabling users to gain a feeling of control over the algorithm. We conducted an online experiment with 163 crowdworkers in which each group completed a collaborative decision-making task and experienced one of the techniques. Through surveys and interviews, we found that the explanation technique was the most effective strategy overall as it reduced user embarrassment, increased the perceived intelligence of the CA, and helped users better understand the detection algorithm. In contrast, the information technique reduced members' contributions and the adjustment technique led to a more negative perceived discussion experience. We also discovered that the interactions with other team members diluted the effects of the techniques on users' performance expectations and acceptance of the CA. We discuss implications for better designing expectation-setting techniques for AI-team collaboration such as ways to improve collaborative decision outcomes and quality of contributions.
ML-Based Teaching Systems: A Conceptual Framework
Authors: Spitzer Philipp , Kühl Niklas , Heinz Daniel , Satzger Gerhard
Published: October 2023

As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical challenge for organizations to preserve the knowledge of retiring experts and pass it on to novices. While this knowledge transfer has traditionally occurred through personal interaction, it lacks scalability and requires significant resources and time. IT-based teaching systems have addressed this scalability issue, but their development is still tedious and time-consuming. In this work, we investigate the potential of machine learning (ML) models to facilitate knowledge transfer in an organizational context, leading to more cost-effective IT-based teaching systems. Through a systematic literature review, we examine key concepts, themes, and dimensions to understand better and design ML-based teaching systems. To do so, we capture and consolidate the capabilities of ML models in IT-based teaching systems, inductively analyze relevant concepts in this context, and determine their interrelationships. We present our findings in the form of a review of the key concepts, themes, and dimensions to understand and inform on ML-based teaching systems. Building on these results, our work contributes to research on computer-supported cooperative work by conceptualizing how ML-based teaching systems can preserve expert knowledge and facilitate its transfer from SMEs to human novices. In this way, we shed light on this emerging subfield of human-computer interaction and serve to build an interdisciplinary research agenda.
Periscope: A Robotic Camera System to Support Remote Physical Collaboration
Authors: Praveena Pragathi , Wang Yeping , Senft Emmanuel , Gleicher Michael , Mutlu Bilge
Published: October 2023

We investigate how robotic camera systems can offer new capabilities to computer-supported cooperative work through the design, development, and evaluation of a prototype system called Periscope. With Periscope, a local worker completes manipulation tasks with guidance from a remote helper who observes the workspace through a camera mounted on a semi-autonomous robotic arm that is co-located with the worker. Our key insight is that the helper, the worker, and the robot should all share responsibility of the camera view-an approach we call shared camera control. Using this approach, we present a set of modes that distribute the control of the camera between the human collaborators and the autonomous robot depending on task needs. We demonstrate the system's utility and the promise of shared camera control through a preliminary study where 12 dyads collaboratively worked on assembly tasks. Finally, we discuss design and research implications of our work for future robotic camera systems that facilitate remote collaboration.
Technology-Enabled Interventions for Sustaining Behaviour Change in Adolescents: A Scoping Review for Research Gaps
Authors: Chin Grace H.Y. , Chow Kenny K.N.
Published: October 2023

Long-term behaviour change for adolescents plays an important role in improving the adolescent's future health. However, long-term behaviour changes are rarely sustained. This study aims to inform human-computer interaction researchers of the current state of research regarding the designing of technology-enabled interventions for sustaining behaviour change for adolescents, as well as provide recommendations for future research directions. Through a scoping review, 22 interventions were identified and analysed to report the behaviour change strategies, characteristics, levels of influence, and formats of technology used, as well as the frameworks used to develop these interventions. Based on the review's findings, three research gaps were identified: (1) the exploration of approaches to restructuring the environment; (2) the exploration of the effects of varying levels of social interactivity between people; and (3) the development of frameworks for building interventions.
The Use and Non-Use of Technology During Hurricanes
Authors: Simko Lucy , Sri Ramulu Harshini , Kohno Tadayoshi , Acar Yasemin
Published: October 2023

Hurricanes can cause catastrophic damage; it is critical for those affected to access information about conditions, loved ones, and resources. Prior work in the HCI and CSCW communities has focused on how social media can be vital during natural disasters; non-social media technologies have been under-researched. To understand how technology other than social media can support or harm people during crises, we explore hurricane survivors' use and disuse of multiple kinds of technologies in online surveys with 138 US participants. We find substantial technology use supporting survivors' comfort and safety other than social media. We also observe that designing technologies for high-resource environments--as with many mainstream apps--causes users to decrease use of potentially critical technologies during utility outages, which are common during hurricanes. With themes of both (a) broad technology use and (b) conditions preventing technology use, we make recommendations for technical design, policy, and research to empower communities susceptible to hurricanes.
Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
Authors: Lee Min Hun , Chew Chong Jun
Published: October 2023

Artificial intelligence (AI) is increasingly being considered to assist human decision-making in high-stake domains (e.g. health). However, researchers have discussed an issue that humans can over-rely on wrong suggestions of the AI model instead of achieving human AI complementary performance. In this work, we utilized salient feature explanations along with what-if, counterfactual explanations to make humans review AI suggestions more analytically to reduce overreliance on AI and explored the effect of these explanations on trust and reliance on AI during clinical decision-making. We conducted an experiment with seven therapists and ten laypersons on the task of assessing post-stroke survivors' quality of motion, and analyzed their performance, agreement level on the task, and reliance on AI without and with two types of AI explanations. Our results showed that the AI model with both salient features and counterfactual explanations assisted therapists and laypersons to improve their performance and agreement level on the task when 'right' AI outputs are presented. While both therapists and laypersons over-relied on 'wrong' AI outputs, counterfactual explanations assisted both therapists and laypersons to reduce their over-reliance on 'wrong' AI outputs by 21% compared to salient feature explanations. Specifically, laypersons had higher performance degrades by 18.0 f1-score with salient feature explanations and 14.0 f1-score with counterfactual explanations than therapists with performance degrades of 8.6 and 2.8 f1-scores respectively. Our work discusses the potential of counterfactual explanations to better estimate the accuracy of an AI model and reduce over-reliance on 'wrong' AI outputs and implications for improving human-AI collaborative decision-making.
User Perspectives on Branching in Computer-Aided Design
Authors: Cheng Kathy , Cuvin Phil , Olechowski Alison , Zhou Shurui
Published: October 2023

Branching is a feature of distributed version control systems that facilitates the "divide and conquer" strategy present in complex and collaborative work domains. Branching has revolutionized modern software development and has the potential to similarly transform hardware product development via CAD (computer-aided design). Yet, contrasting with its status in software, branching as a feature of commercial CAD systems is in its infancy, and little research exists to investigate its use in the digital design and development of physical products. To address this knowledge gap, in this paper, we mine and analyze 719 user-generated posts from online CAD forums to qualitatively study designers' intentions for and preliminary use of branching in CAD. Our work contributes a taxonomy of CAD branching use cases, an identification of deficiencies of existing branching capabilities in CAD, and a discussion of the untapped potential of CAD branching to support a new paradigm of collaborative mechanical design. The insights gained from this study may help CAD tool developers address design shortcomings in CAD branching tools and assist CAD practitioners by raising their awareness of CAD branching to improve design efficiency and collaborative workflows in hardware development teams.
Why should I bother to break the norm?: Exploring the Prospects of Adopting Technology-Driven Solutions by Indian Shrimp Farmers
Authors: Medarametla Lokesh , Ahmed Saquib , Dey Sanorita
Published: October 2023

India produces a large amount of shrimp every year and exports them globally. Yet, concerns have been raised about shrimps produced in India not qualifying the global safety standards. In this paper, we took an ethnographic approach to understand the traditional farming practices followed by shrimp farmers in India. We interviewed 29 shrimp farmers from Andhra Pradesh in India for eight months. We learned that most experienced and large-scale shrimp farmers in India prefer to follow traditional practices in their shrimp farms. They prefer to adopt technology-driven solutions in their farming only if absolutely needed. However, we observed that young, small-scale farmers are more open to trying new technologies in their farming. We discussed several areas where initiatives can be taken to encourage more Indian shrimp farmers to adopt new technology-driven solutions in their farming.
Work Hard, Scare Hard? An Investigation of How Mental Workload Impacts Jump Scare Intensity
Authors: Terkildsen Thomas , Engelst Lene , Clasen Mathias
Published: October 2023

Despite the prevalence and relevance of jump scares in horror video games, there is little empirical research on them. While HCI research commonly uses horror games as experimental stimuli, even less scientific research exists on what makes a jump scare in a game more or less scary. The present between-subject study (n=60) addresses this by investigating whether jump scare intensity—measured physiologically and subjectively—scales with task difficulty. We triggered in-game jump scares at increasing levels of mental workload across four counterbalanced conditions, manipulated using N-back tasks of varying difficulty. Results demonstrate a significant linear relationship between mental workload and physiological arousal. However, this is not the case for subjective perception of arousal elicited by the jump scare. These findings have design implications for horror games. They show that the level of physiological arousal caused by a jump scare can be controlled by changing the difficulty of an in-game task that necessitates a substantial amount of mental work at the same time.